fix(intro): keep restricted volumes to areas that fit the scene

Fort Bragg's reservation polygon is larger than the scene, which turned
every road into a convoy and floated curtain walls past the ground edge.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01KqP857pippaUs6konSDfe8

.env.example

@@ -83,12 +83,6 @@ OPENAI_REALTIME_TRANSCRIBE_MODEL=gpt-4o-mini-transcribe
 # keep them while debugging; delete the log when you are done.
 GEV_VOICE_LOG_CONTENT=
 OPENAI_HUD_SUMMARY_MODEL=gpt-5-nano
-# Optional: Gemini Live voice, selected in the GEV MIC provider chooser.
-# Server-only key. Do not prefix with VITE_. Provider Settings can save it.
-GEMINI_API_KEY=
-GEMINI_LIVE_MODEL=gemini-3.8-live
-# Token starts per IP per minute; 0 disables the throttle, not provider quotas.
-# GEV_RATELIMIT_GEMINI_PER_MIN=30
 # Per-IP rate limit for the OpenAI cost endpoints
 # (/api/realtime/token + /api/openai/hud-summary), in requests per minute.
 # DEFAULTS TO 30, the value the Pinokio build also ships. That clears ordinary
@@ -124,8 +118,8 @@ OPENSKY_AUTH_MODE=oauth
 OPENSKY_CLIENT_ID=
 OPENSKY_CLIENT_SECRET=
 
-# Launch Library 2: leave blank for standard public access (no key needed).
+# Optional: higher Launch Library 2 request allowance. Public access works
-# Optional paid Patreon tokens raise request limits; there is no free API key.
+# without a token.
 LL2_API_TOKEN=
 
 # Optional: OpenSky credentials JSON file path (alternative to above)
@@ -207,7 +201,6 @@ AISSTREAM_API_KEY=
 # CCTV_TFL_ENABLED=1                                   # set 0 to disable Transport for London JamCams
 # CCTV_TFL_MAX_SOURCES=250                             # cap cameras loaded from TfL
 # CCTV_ONTARIO_ENABLED=1                               # set 0 to disable Ontario 511 cameras
-# ONTARIO_511_API_KEY=                                 # free developer key: sign up at 511on.ca/my511/register, then request it at 511on.ca/developers/doc
 # CCTV_ONTARIO_MAX_SOURCES=1000                        # cap cameras loaded from Ontario 511
 # CCTV_FINTRAFFIC_ENABLED=1                            # set 0 to drop the Fintraffic (Finland) pack
 # CCTV_FINTRAFFIC_MAX_SOURCES=300                      # cap cameras loaded from the Fintraffic catalog
@@ -235,7 +228,6 @@ AISSTREAM_API_KEY=
 # CCTV_VEGVESEN_ENABLED=1                              # set 0 to disable the Statens vegvesen (Norway) road cameras
 # CCTV_VEGVESEN_MAX_SOURCES=900                        # cap cameras loaded from Statens vegvesen (default loads all ~850 live; max 1000)
 # CCTV_VEGVESEN_VIDEO=1                                # set 0 to show stills instead of live HLS for Statens vegvesen video cameras
-# CCTV_VEGVESEN_HEIGHTS=1                              # set 0 to skip Kartverket ground heights for Statens vegvesen cameras (flat prior instead)
 # CCTV_VEGVESEN_URL=                                   # override the Statens vegvesen catalog URL
 # CCTV_NYC_ENABLED=                                    # off by default; set 1 only if you hold a NYC DOT data-sharing agreement ([email protected]) for the camera feed
 # CCTV_NYC_MAX_SOURCES=250                             # cap cameras loaded from the NYC TMC catalog (nearest borough cores first)
@@ -245,8 +237,6 @@ AISSTREAM_API_KEY=
 # CCTV_TORONTO_LIST_URL=                               # override the Toronto RESCU camera list URL
 # CCTV_LITHUANIA_ENABLED=                              # off by default; set 1 to load Via Lietuva / Eismoinfo road cameras (photo licence unconfirmed; see DATA_SOURCES.md)
 # CCTV_LITHUANIA_MAX_SOURCES=400                       # cap Lithuanian cameras; no API key required
-# CCTV_FLORIDA_ENABLED=                                # off by default; set 1 to load FL511 (Florida) cameras (individual, personal use only; any other use, including a public deployment, needs FDOT's express written consent; see DATA_SOURCES.md)
-# CCTV_FLORIDA_MAX_SOURCES=500                         # cap cameras loaded from the FL511 catalog (nearest regional anchors first)
 # CCTV_MAX_SOURCES=4000                                # catalog-wide ceiling, shared round-robin across packs
 # CCTV_PREFER_AUSTIN=1                                 # prioritize Austin cameras in the registry
 # CCTV_FORCE_AUSTIN=                                   # force live default sources when a source-pack JSON is configured

DATA_SOURCES.md

@@ -48,7 +48,6 @@ How to read this:
 | **GDELT Project DOC 2.0**                                             | Fail-soft fallback for location-matched cockpit headlines                                                                           | [GDELT Terms of Use](https://www.gdeltproject.org/about.html#termsofuse): unrestricted academic/commercial/governmental dataset use, with citation and link required; linked articles retain publisher terms                                                                                                                                          | "GDELT Project" plus each article's linked publisher/domain                                                                                 |
 | **City of Austin Open Data**                                          | CCTV camera catalog + frames                                                                                                        | City of Austin Open Data Terms of Use                                                                                                                                                                                                                                                                                                                 | "City of Austin, TX — data.austintexas.gov"                                                                                                 |
 | **TxDOT ITS (its.txdot.gov)**                                         | CCTV camera catalogs + frames, Texas districts                                                                                      | Public TxDOT traffic camera data                                                                                                                                                                                                                                                                                                                      | "Texas Department of Transportation" (courtesy)                                                                                             |
-| **FL511 (Florida DOT)** | CCTV camera catalog + frames, Florida statewide | FL511 content, individual personal use only; any other use needs FDOT's express written consent ([terms](https://fl511.com/privacy#disclaimer)). **Off by default**; set `CCTV_FLORIDA_ENABLED=1` to enable | "Florida DOT — FL511.com" (courtesy) |
 | **City of Tallinn (ristmikud.tallinn.ee)**                            | CCTV camera catalog + frames, Tallinn intersections                                                                                 | Public City of Tallinn traffic camera data                                                                                                                                                                                                                                                                                                            | "City of Tallinn — ristmikud.tallinn.ee" (courtesy)                                                                                         |
 | **Transpordiamet / Tarktee**                                          | CCTV camera catalog + frames, Estonia road-weather cameras                                                                          | Public Transpordiamet / Tarktee road camera data                                                                                                                                                                                                                                                                                                      | "Transpordiamet / Tarktee — tarktee.transpordiamet.ee" (courtesy)                                                                           |
 | **Stadt Warendorf webcam**                                            | Webcam frames, Marktplatz / Historisches Rathaus (`config/cctv_sources.warendorf.json`)                                             | Public municipal webcam data                                                                                                                                                                                                                                                                                                                          | "Stadt Warendorf — webcam.warendorf.de" (courtesy)      |
@@ -64,7 +63,6 @@ How to read this:
 | **King County Road Services** (`services.arcgis.com`, King County GIS) | CCTV camera catalog + frames, unincorporated King County WA road network                                                            | [KCGIS Center terms](https://kingcounty.gov/en/dept/kcit/data-information-services/gis-center/about/terms-conditions-copyrights) — attribution required; public ArcGIS layer                                                                                                                                                                          | "King County Road Services" (partner-city cameras name their owner)                                                                         |
 | **WSDOT** (`data.wsdot.wa.gov`)                                       | CCTV camera catalog + frames, Washington State highways                                                                             | [WSDOT travel information disclaimer](https://wsdot.wa.gov/about/policies/travel-information-disclaimer) — public "low volume" feed; catalog cached, frames on WSDOT's own image host only                                                                                                                                                            | "Washington State Department of Transportation (Travel Center)" (courtesy)                                                                  |
 | **Statens vegvesen** (catalog `ogckart-sn1.atlas.vegvesen.no`, frames `kamera.atlas.vegvesen.no`, HLS `kamera.vegvesen.no`) | CCTV camera catalog + frames + live HLS video, Norway road cameras                                                                                   | [NLOD 2.0](https://data.norge.no/nlod/en/2.0) — attribution REQUIRED | "Contains data under the Norwegian licence for Open Government data (NLOD) distributed by Statens vegvesen" |
-| **Kartverket** (`ws.geonorge.no/hoydedata/v1/punkt`)               | Terrain heights (NN2000) used as the ground prior for Statens vegvesen cameras                                                     | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — attribution REQUIRED | "© Kartverket", modified (heights over water set to 0 m, rounded to 0.1 m) |
 | **NYC DOT Traffic Management Center** (`webcams.nyctmc.org`) | CCTV camera catalog + frames, New York City five boroughs | NYC DOT requires developers to sign a [data-sharing agreement](https://www.nyc.gov/html/dot/html/about/datafeeds.shtml) for the camera feed. **Off by default**; enable only under your own agreement | "NYC DOT Traffic Management Center" + NYC DOT's required application disclaimer (in the Data attribution popover) |
 | **City of Toronto Open Data** (`opendata.toronto.ca`)                 | CCTV camera catalog + frames, Toronto city streets                                                                                  | [Open Government Licence – Toronto](https://www.toronto.ca/city-government/data-research-maps/open-data/open-data-licence/) — attribution REQUIRED                                                                                                                                                                                                    | "Contains information licensed under the Open Government Licence – Toronto"                                                                 |
 | **GBFS (Lyft / BCycle / Social Bicycles / PBSC)**                     | Bikeshare availability                                                                                                              | Per-feed (attribution-only)                                                                                                                                                                                                                                                                                                                           | Credit the operator (e.g. Austin BCycle) + its `license_url`                                                                                                   |
@@ -154,7 +152,7 @@ The optional Local ADS-B layer and the broadcast-FM receiver use radio you recei
 - **adsbdb enrichment.** `/api/adsbdb` resolves an ICAO hex to aircraft type, model name and registration, and the tracked flight's callsign to an airline and an origin/destination pair. Fan-out is deliberately small because adsbdb is a free community API that publishes no quota: at most 4 requests in flight, dispatches dripped to roughly 5/s, and each key asked for at most once per session, with route lookups reserved for the tracked aircraft. The dev-server proxy caches each key for 24 hours in `.gev-cache/adsbdb.json`, negative answers included, so fresh entries survive server restarts. That gitignored cache remains local to the deployment and is not bundled with this repo. adsbdb publishes no general service license; its README says the route data may not be copied, published, or incorporated into other databases without the explicit permission of David J Taylor, Edinburgh. Deployers are responsible for obtaining any permission their use requires. Enrichment is best-effort and fail-silent — a flight that gets no answer keeps what the flight feed already gave it.
 - **Launch Library 2.** `/api/launches` makes a server-side rolling-30-day query against the supported v2.3 detailed launch endpoint, caches successful responses for 15 minutes in memory and on disk, and serves the last successful response during a throttle or transient outage. Anonymous access is limited to 15 calls/hour; deployments can provide `LL2_API_TOKEN` for authenticated access. The Space Devs' published terms permit using and sharing the API data in any form, ask users not to forward it without adding value, disclaim complete accuracy, and encourage—but do not require—attribution. This app keeps a courtesy credit. Payload and stage/recovery records are shown only when supplied. Failed launches expose their source status and never receive fallback orbit geometry or a live/estimated marker. LL2 supplies launch context and event timing, not continuous ascent telemetry or live orbital state.
 - **TfL JamCams.** The camera list comes from the keyless `api.tfl.gov.uk` endpoint (an optional `TFL_APP_KEY` raises its rate limit); frames come from TfL's public S3 bucket. The "Powered by TfL Open Data" attribution is required by TfL's terms and is registered in the Data attribution popover.
-- **Ontario 511 CCTV.** The camera list comes from the `511on.ca/api/v2/get/cameras` endpoint, which now requires a free developer key (`ONTARIO_511_API_KEY`: sign up at 511on.ca/my511/register, then request it while logged in at 511on.ca/developers/doc; throttled to 10 calls a minute). Without the key the pack is skipped. Frames are server-registered still images under `511on.ca/map/Cctv/`. The source is live-fetched at runtime and attributed under the Open Government Licence - Ontario. Access is governed by Ontario 511's Developer's Access Agreement (511on.ca/developers/resources): the data stays under the Open Government Licence - Ontario unless otherwise specified; key requests are reviewed case by case and ask for the intended use and any third parties that will receive the data; attribution by link to 511on.ca is encouraged, and the Ontario 511 logo may not be altered or used to imply endorsement (this app links and shows no logo); and the data is provided "as is", a disclaimer distributors should pass on, which the credit does.
+- **Ontario 511 CCTV.** The camera list comes from the keyless `511on.ca/api/v2/get/cameras` endpoint; frames are server-registered still images under `511on.ca/map/Cctv/`. The source is live-fetched at runtime and attributed under the Open Government Licence - Ontario.
 - **DelDOT live video cameras.** The keyless `tmc.deldot.gov/json/videocamera.json` catalog supplies active cameras and official `https://video.deldot.gov/live/…/playlist.m3u8` links. The local server transiently buffers bounded MPEG-TS segments in memory and deletes them on session release or idle expiry. No recordings are retained. `CCTV_DELDOT_ENABLED=0` disables the pack. Public availability is not a blanket redistribution license; deployment beyond personal local viewing needs confirmation of applicable DelDOT terms.
 - **Fintraffic weathercams.** The camera list is one keyless GeoJSON request to `tie.digitraffic.fi/api/weathercam/v1/stations` (809 stations / 2,275 presets), sent with the `Digitraffic-User: gods-eye-view` header the service asks clients to identify themselves with and with gzip; frames are stills on `weathercam.digitraffic.fi`, refreshed on each station's 600 s collection interval, which is also the client's ambient-still refresh cadence for this pack (the active camera keeps the usual 10-second refresh). One preset (a fixed camera view) is one camera; stations not `GATHERING` and presets not `inCollection` are dropped. Attribution is required by the CC BY 4.0 licence and is registered in the Data attribution popover. `CCTV_FINTRAFFIC_ENABLED=0` is the kill switch.
 - **DriveBC highway cameras.** The camera list comes from the keyless `https://www.drivebc.ca/api/webcams/` endpoint served by the DriveBC.ca site ([bcgov/DriveBC.ca](https://github.com/bcgov/DriveBC.ca)); frames come from `https://www.drivebc.ca/images/<id>.jpg`, built from the numeric camera id. DataBC's [DriveBC HighwayCams](https://catalogue.data.gov.bc.ca/dataset/bc-highwaycams) catalogue entry publishes the same cameras under the Open Government Licence – British Columbia, but its CSV still lists the retired `images.drivebc.ca` frame URLs, which now return a placeholder. The licence's attribution statement is required and is registered in the Data attribution popover. By default the 250 cameras nearest Vancouver and Victoria load; `CCTV_DRIVEBC_MAX_SOURCES` changes the cap and `CCTV_DRIVEBC_ENABLED=0` turns the pack off. Some cameras in the feed are supplied by partners (TransLink, the City of Vancouver, the City of Surrey, Parks Canada / Alberta Motor Association and others); the feed's per-camera credit is carried onto the camera record and shown beside the provider in the CCTV panel.
@@ -164,12 +162,10 @@ The optional Local ADS-B layer and the broadcast-FM receiver use radio you recei
 - **Warendorf webcam.** The Stadt Warendorf Marktplatz webcam, registered from the curated `config/cctv_sources.warendorf.json` (the Kreis Warendorf registration-office cameras from the contributing PR are indoor waiting rooms and were left out); only the municipal image host is proxied, frames are fetched at request time and never stored or redistributed. Disable with `CCTV_WARENDORF_ENABLED=0`.
 - **Live Traffic NSW cameras.** The camera list is the keyless public `data.livetraffic.com/cameras/traffic-cam.json` feed (Transport for NSW open data, CC BY 4.0); frames are stills on `webcams.transport.nsw.gov.au`, and only that host is registered. That image host answers non-browser clients with an HTML placeholder, so the proxy identifies as a browser for that one host and as itself everywhere else. Frames are fetched at request time and never stored or redistributed. Disable with `CCTV_NSW_ENABLED=0`.
 - **Open Calgary traffic cameras.** Keyless. The camera list is the public Socrata dataset `k7p9-kppz` on `data.calgary.ca`; frames are stills on the city's own `trafficcam.calgary.ca` host, and only that host is registered. Most rows publish an `http://` frame URL and the host redirects those to HTTPS, so URLs are upgraded and pinned to that origin before registration. Frames are fetched at request time and never stored or redistributed. The dataset publishes no camera facing: the `quadrant` field and the quadrant suffix on each camera name are Calgary's address grid, not a bearing, so headings use the shared id-hash fallback at low confidence and are corrected with the in-app calibration gizmo. The licence requires the attribution statement above. Disable with `CCTV_CALGARY_ENABLED=0`.
-- **FL511 Florida cameras.** Off by default; set `CCTV_FLORIDA_ENABLED=1` to load them. The camera list is the keyless FL511 traffic camera layer on ArcGIS (`services.arcgis.com/.../FL511_Traffic_Cameras`), published from a Florida Division of Emergency Management account rather than by FL511 directly, and the service carries no licence text of its own. It is paged up to 2,000 rows at a time, ordered by the layer's object id and following ArcGIS's `exceededTransferLimit`, to cover the ~4,000-camera statewide set. Frames are stills on two Divas Cloud hosts (`images-dis.divas.cloud`, `snapshots.divas.cloud`); both are host-pinned and a row whose image resolves elsewhere is dropped. `CCTV_FLORIDA_MAX_SOURCES` caps the pack (default 500, anchored per region across the state). Each catalog page is read under a 2 MiB cap and redirects are refused. Frames are fetched live at request time and never stored or redistributed. FL511's terms (fl511.com/privacy#disclaimer) license its content for individual, personal use only; any other use, including a public deployment, needs FDOT's express written consent.
 - **Catalonia (Servei Català de Trànsit) cameras.** The camera list is the keyless `https://www.gencat.cat/transit/opendata/cameres.xml` WFS/GML feed, fetched over https with redirects refused and the body read capped at 1 MiB, since the list decides ids, coordinates and which allowlisted frame path is proxied. It carries a `font` field naming the real publisher per camera; this pack keeps SCT's own highway cameras plus hotlinked Barcelona (IMI) and Terrassa municipal cameras (~130 total), each confirmed to return a real frame, so frame URLs are checked against a small host allowlist (`mct.gencat.cat`, `www.bcn.cat`, `emap.terrassa.cat`) rather than one pinned origin (a link carrying `user:pass@` userinfo or an explicit port, or pointing outside that host's frame directory, is rejected even on an allowed host; an SCT `sctidcam` must be a bare `.gif`/`.jpg` filename), and every non-SCT camera carries its real owner as a `credit` shown beside the shared `provider`. The feed carries no compass heading, so every camera loads at low heading confidence (same as TfL and Fintraffic). SCT's own feed link (`RenderService`) needed a workaround: it always 302s to a second endpoint (`TransitCamera`) on a Location the upstream hardcodes as plain http even when requested over https — refused by `fetchWithinHost`'s same-origin (scheme-included) redirect policy — and separately, `mct.gencat.cat`'s TLS setup fails the handshake with Node's fetch outright (`ERR_SSL_WRONG_SIGNATURE_TYPE`) even though other HTTP clients complete it. The loader therefore builds the `TransitCamera` URL itself, over plain http, from `RenderService`'s `sctidcam` id, rather than registering the (broken) upstream link — the only transport this one host actually serves to this runtime. Camera ids are built from the SCT camera file or the partner image path, not the feed's `fid` (which embeds an upstream server-start stamp and changes on every upstream restart), and rows the feed lists more than once collapse to one camera. The feed carries no camera status field, so a camera its publisher has taken offline still registers and shows the publisher's own "image unavailable" still (SCT and Barcelona both serve one with HTTP 200), the same as other packs without a status field. Frames are fetched at request time and never stored or redistributed. The feed itself states no licence; the pack relies on the Generalitat de Catalunya open-data portal's terms for this dataset (the licence and attribution above). Disable with `CCTV_CATALONIA_ENABLED=0`.
 - **King County road cameras.** Keyless. The camera list is one public ArcGIS FeatureServer GeoJSON query (King County DOT Road Services, "King County and WSDOT Traffic Cameras"). The `outFields` list is explicit on purpose: the layer also carries asset-administration columns — including staff names — that are never fetched. Only live, active cameras with frames on the county's own `info.kingcounty.gov` image handler are registered (the feed writes `http://`; the handler serves HTTPS, so URLs are upgraded and pinned before registration). WSDOT-owned rows in the layer are skipped because their frames are WSDOT-hosted, outside the pinned image origin; partner-city cameras hosted on the county image handler (e.g. Newcastle) name their owner as the per-camera credit. The layer publishes no facing, so headings use the shared id-hash fallback at low confidence. Uniquely, the county publishes each camera's hardware `Manufacturer`/`Model` (Cohu 3950/3965, Bosch AUTODOME, Axis PTZ domes); both are carried on the source (and served by `/api/cctv/sources`) as `model` and `manufacturer` for identified-hardware consumers (vendor-generic strings such as `PTZ` name no model and are omitted). Frames are fetched at request time and never stored or redistributed. Disable with `CCTV_KINGCOUNTY_ENABLED=0`.
 - **WSDOT highway cameras.** Keyless. The camera list is the Esri JSON layer `data.wsdot.wa.gov/travelcenter/Cameras.json` — the same layer WSDOT's own Travel Center map consumes (~1,700 point features, EPSG:3857 geometry converted to WGS84 on load; the body carries Windows-1252 bytes and is decoded as such). Only frames on WSDOT's own `images.wsdot.wa.gov` host are registered — the catalog also lists ~70 partner cameras (Oregon DOT, City of Seattle, lodges, airports) whose own terms apply, and those are skipped rather than proxied. WSDOT's layer metadata marks the feed for "low volume" use (see WSDOT's [travel information disclaimer](https://wsdot.wa.gov/about/policies/travel-information-disclaimer)). The catalog is fetched once per CCTV catalog refresh (every 15 minutes), and a camera's frame is fetched only when that camera is viewed; frames are never stored or redistributed. The live feed's `CompassDirection` is a single cardinal (N/E/S/W), `B` (both directions — most rows), `O`, or null. A single cardinal gives a high-confidence heading (the diagonals NE/SE/SW/NW are mapped too should they appear); `B`, `O`, null, and any other code carry no single facing and use the shared id-hash fallback at low confidence. By default the 250 cameras nearest Seattle and Spokane load; `CCTV_WSDOT_MAX_SOURCES` changes the cap (8–1,200) and `CCTV_WSDOT_ENABLED=0` turns the pack off. A keyed WSDOT Traveler Information API serves the same population for higher-volume use and is deliberately not required here.
 - **Statens vegvesen road cameras.** Keyless. The camera list is one GeoJSON request to the OGC API Features view of the official DATEX 3.1 CCTV site table (`ogckart-sn1.atlas.vegvesen.no/ogc/features/v1/collections/datex_3_1:CctvSimple/items`), so no DATEX account is needed; frames are stills on `kamera.atlas.vegvesen.no/api/images/<cameraId>`, and only that exact path per camera is registered. Cameras the feed reports as faulty are dropped. About 135 working cameras also publish live HLS (`kamera.vegvesen.no/public/<cameraId>/manifest.m3u8`, MPEG-TS); those play as live video through the bounded in-memory HLS relay, with the still as the snapshot fallback, and only that exact manifest path per camera is registered. `CCTV_VEGVESEN_VIDEO=0` keeps every camera on stills. `orientationDescription` names the place a camera faces, not a bearing, so it goes into the label and headings use the id-hash fallback at low confidence. By default every live camera loads (~850); `CCTV_VEGVESEN_MAX_SOURCES` (8–1000) lowers the cap, keeping the cameras nearest Oslo, Bergen, Stavanger, Trondheim, Kristiansand, Bodø and Tromsø and `CCTV_VEGVESEN_ENABLED=0` turns the pack off. Frames are fetched at request time and never stored or redistributed. The NLOD attribution is registered in the Data attribution popover.
-- **Kartverket ground heights for Statens vegvesen cameras.** The camera feed's points are 2D, so the loader asks Kartverket's keyless point-height API (`ws.geonorge.no/hoydedata/v1/punkt`, CC BY 4.0) for the terrain height at each camera. Requests carry 20 points: the API accepts 50, but above ~20 it answers the extra points from contour lines (`hoydekurver`, metres to ~20 m off) or not at all. Eight requests run at a time, about 36 for the whole country: a cold lookup took 6–13 s in testing (single requests 0.6–9.5 s). Answers are matched by the coordinates the API echoes and recorded only for points that request asked about. Over water the API returns the sea-floor depth (`dybdekurver` or `Havflate`), which is replaced by 0 m, the water surface; for the ~14 bridge cameras that is below the deck, but much closer than the sea floor or the flat prior. Heights are cached in memory by position for the life of the server, and points with no height (a few ferry quays and bridges, or a point a 200 answer leaves out) for 6 h, so the 15-minute catalog refresh only asks about new or moved cameras. The first failing request (a 408, 429 or 5xx, a network error, a request over 10 s, or an unreadable or oversized body) stops the lookup, with no retries, and no new lookup starts until the backoff ends (Retry-After when sent, else 30 min, longer than the refresh; bounded to 1 min–1 h). Any other 4xx marks that request's points as having no height and the lookup carries on. The whole lookup has a 30 s deadline; a lookup cut short by it resumes on the next refresh without a backoff. The lane waits at most 12 s, counted from the start of the loader, and only when more than 10% of the cameras have no answer yet; a few new cameras or expired misses are looked up in the background. A slower lookup keeps filling the cache, and the cameras it had not reached keep the flat prior until the next 15-minute refresh (about 190 of 865 on one slow first run). Only coordinates are sent, with the same User-Agent as the other CCTV requests. `CCTV_VEGVESEN_HEIGHTS=0` turns the lookup off. The Kartverket credit, with a note that heights over water are set to 0 m and heights are rounded to 0.1 m, is shown beside the Statens vegvesen entry in the Data attribution popover.
 - **NYC DOT Traffic Management Center cameras.** Off by default. NYC DOT's [developer data feeds page](https://www.nyc.gov/html/dot/html/about/datafeeds.shtml) asks developers who want the camera feed to contact `[email protected]` and sign a data-sharing agreement. This project does not hold one that covers downstream installations, so the pack loads only when an operator who holds their own agreement sets `CCTV_NYC_ENABLED=1`; with the flag unset, empty or any other value, the server makes no request to NYC DOT. The endpoint needs no key. The camera list is the public `webcams.nyctmc.org/api/cameras` catalog (~980 cameras across the five boroughs); frames are stills at `webcams.nyctmc.org/api/cameras/<uuid>/image`, synthesized from a validated UUID rather than taken from the payload, and only that host is registered. Cameras the feed reports as offline are dropped. The catalog publishes no camera facing, so headings use the shared id-hash fallback at low confidence and are corrected with the in-app calibration gizmo. Once enabled, the 250 cameras nearest the borough cores load; `CCTV_NYC_MAX_SOURCES` (8–400) changes the cap. Frames are fetched at request time and never stored or redistributed. NYC DOT asks every application that uses its data to carry its disclaimer; it is registered verbatim in the Data attribution popover.
 - **City of Toronto RESCU cameras.** Keyless. The camera list is the City's public `tmcearthcameras.json` on `opendata.toronto.ca` (dataset "Traffic Cameras", Transportation Services), served as JSONP and unwrapped with an anchored pattern. This is the municipal network the Ontario 511 pack does not carry: downtown arterials plus the Gardiner, DVP, Allen and Lake Shore. The list publishes no frame URL, so frame URLs are BUILT from the documented `CameraImages/loc####.jpg` convention and a strictly-digits camera number, pinning the frame proxy to the portal origin by construction; the list fetch refuses redirects and bounds the body it buffers. Frames are fetched at request time and never stored or redistributed. The dataset publishes no camera facing: the `D1`-`D4` fields are the directions of the *comparison* images (static reference stills captured in 2016 under a different path), not a bearing for the live pan-tilt-zoom frame, so headings use the shared id-hash fallback at low confidence and are corrected with the in-app calibration gizmo. A camera that is temporarily out of service still answers 200 with a byte-identical "Image Unavailable" placeholder rather than an error (about 6% of the network at any moment), so such a camera reads as healthy; the frame it shows is the agency's, not a synthesized one. The licence requires the attribution statement above. Disable with `CCTV_TORONTO_ENABLED=0`.
 - **Camera frame content.** Public camera frames can contain people, vehicles and license plates, and the camera layer does nothing with them beyond putting them on the map. A successful upstream response is relayed as the provider served it: nothing in the camera pipeline blurs, redacts, enhances or restores it, and nothing there runs face, plate or object detection or otherwise recognises or classifies what is in the picture. (The ALPR layer described below maps where plate-reader cameras are, from locations contributors tagged in OpenStreetMap; it reads nothing from any camera frame.) When an upstream has no frame for a camera, what you see instead is a Google Street View still or the app's own placeholder card; the panel's source badge names which of them you are looking at, and a refresh that fails after a frame has arrived leaves the last good picture on screen rather than replacing it. The browser resamples each frame for display: onto a fixed 1920x1080 surface for the camera's projection plane in the scene, and onto a 192x108 canvas for the small ambient card. That scaling is the only change made to the picture, and the only pixels the camera layer reads back are a 64x36 downscale hashed to tell whether the picture has changed. Live streams are piped through; the still path reads the image into memory to pass it on — TxDOT wraps its JPEG in a JSON envelope, which is decoded there — and no frame is written to disk (the disk cache, `.gev-cache/`, holds feed JSON for other layers and never camera imagery). Outside that pipeline, the voice assistant is the one feature that sends imagery anywhere: when it answers a question about what is in view it may attach a downscaled screenshot of the rendered scene — including any camera plane on screen — to the request it sends to the voice model. Frames are fetched only from server-registered camera URLs — a client cannot hand the proxy a URL (see [SECURITY.md](SECURITY.md)). What the app does stays inside the line README draws: no named-person search, no face recognition, no tracking individuals.

README.md

@@ -309,10 +309,6 @@ _Why cockpit mode exists: you're riding a real aircraft over real terrain — an
 
 ## 🎙️ Talk to It
 
-The standalone app offers **OpenAI** and **Gemini** in the GEV MIC provider chooser. OpenAI is the initial default; your choice is saved in this browser. To use Gemini, add `GEMINI_API_KEY` in Provider Settings or your local `.env` file, then select Gemini. `GEMINI_LIVE_MODEL` defaults to `gemini-3.8-live`. The permanent key stays on the local server, which issues a constrained, single-use session credential.
-
-Changing provider ends the current conversation. If voice is on, the new provider starts with the same open-mic or push-to-talk mode; a held Space key is not carried over. Gemini uses the same map actions and captions, but has no OpenAI cost meter or MINI tier. When Gemini reports that its session has expired, start voice again for a new conversation. The provider chooser does not change the OpenAI-backed AI HUD summary.
-
 > Voice can use an **OpenAI API key** or, on the same machine, an opt-in signed-in **ChatGPT/Codex OAuth** session. The API-key path remains the default. Selecting ChatGPT OAuth in Provider Settings reuses an existing local sign-in or starts the Codex browser sign-in flow and selects OAuth when it completes. The OpenAI key still drives the **AI HUD summary**: a terse, five-word intelligence-style readout of the current view that regenerates as you move.
 
 The OAuth option is experimental. OpenAI documents ChatGPT plan usage for the [Responses API](https://developers.openai.com/siwc/token-sharing-open-source/models-and-inference); a supported third-party Realtime contract for reusing Codex tokens has not been confirmed. A successful token mint does not establish billing or support terms.
@@ -381,7 +377,7 @@ Twenty layers and map sources. **Eighteen have a keyless path.** Some offer addi
 | 🌍 **Earthquakes**          | Global seismic activity, last 24h                                                                                                                                                                                                                                                                                                                                                   | USGS                                    | 🟢                                                                                                  |
 | ◍ **Air quality**           | Live AQHI on the published 1–10+ health-risk scale, with a Weather-panel card showing the band legend and the highest readings in view. **Canada only** — ECCC is the first registered provider | ECCC MSC GeoMet                          | 🟢                                                                                                  |
 | 🚗 **Traffic**              | Simulated vehicles on OSM roads. With TomTom, live flow speeds drive the simulation and congestion colors below ~8 km; individual vehicle positions are not live observations                                                                                                                                                                                                       | TomTom + OSM                            | 🟢 simulation · 🟡 live flow speeds                                                                 |
-| 📹 **CCTV Mesh**            | ~4,000 public cameras (shared cap) projected _into_ the 3D space — Austin · Texas (TxDOT) · California (Caltrans) · London (TfL) · Ontario (511, free developer key) · Finland (Fintraffic) · British Columbia (DriveBC) · Estonia (Tallinn, Tarktee) · Delaware (DelDOT live video) · New South Wales (Live Traffic NSW) · Calgary · Norway (Statens vegvesen) · Toronto · King County (WA) · Washington (WSDOT) · Catalonia (Servei Català de Trànsit), plus opt-in New York City (NYC DOT TMC, needs your own NYC DOT agreement), opt-in Lithuania (Via Lietuva / Eismoinfo, photo licence unconfirmed) and opt-in Florida (FL511, individual personal use only; other use needs FDOT's written consent). Positions are published; poses are estimated priors **you calibrate by dragging a gizmo on the camera itself** | City APIs                               | 🟢                                                                                                  |
+| 📹 **CCTV Mesh**            | ~4,000 public cameras (shared cap) projected _into_ the 3D space — Austin · Texas (TxDOT) · California (Caltrans) · London (TfL) · Ontario (511) · Finland (Fintraffic) · British Columbia (DriveBC) · Estonia (Tallinn, Tarktee) · Delaware (DelDOT live video) · New South Wales (Live Traffic NSW) · Calgary · Norway (Statens vegvesen) · Toronto · King County (WA) · Washington (WSDOT) · Catalonia (Servei Català de Trànsit), plus opt-in New York City (NYC DOT TMC, needs your own NYC DOT agreement) and opt-in Lithuania (Via Lietuva / Eismoinfo, photo licence unconfirmed). Positions are published; poses are estimated priors **you calibrate by dragging a gizmo on the camera itself** | City APIs                               | 🟢                                                                                                  |
 | 📷 **Mapped ALPR Cameras**  | License-plate-reader camera locations tagged by OpenStreetMap contributors, loaded one city-sized view at a time, with **SHOW NEAREST**. Locations and tags only: no plate data, no video                                                                                                                                                                                           | OpenStreetMap (incl. DeFlock mapping)   | 🟢                                                                                                  |
 | 📷 **Street Level**         | Street-level photos behind one panel, one chip per provider: coverage on the streets, image cones, an embedded viewer and **FOLLOW**. Mapillary, Google Street View, KartaView and Panoramax | Mapillary · Google · KartaView · Panoramax | 🟢 KartaView, Panoramax · 🟡 Mapillary token · 🔴 Google Maps key |
 | 📻 **Radio**                | Geolocated world radio with an **analog tuner** — drag the needle across up to 750 stations and the globe flies to each broadcaster                                                                                                                                                                                                                                                 | Radio Browser / broadcasters            | 🟢                                                                                                  |
@@ -389,7 +385,7 @@ Twenty layers and map sources. **Eighteen have a keyless path.** Some offer addi
 | 🚲 **Bikeshare**            | Live station availability                                                                                                                                                                                                                                                                                                                                                           | GBFS                                    | 🟢                                                                                                  |
 | 🧭 **Directions**           | Click A and B on the globe for a street-following drive, walk or cycle route draped on the terrain with turn-by-turn steps — then FLY the camera along it. No key, no geocoder, no mic                                                                                                                                                                                              | OSRM on FOSSGIS servers (OpenStreetMap) | 🟢                                                                                                  |
 | 🔥 **Active Fires**         | Live NASA FIRMS detections, trailing 24h                                                                                                                                                                                                                                                                                                                                            | NASA FIRMS                              | 🟡                                                                                                  |
-| 🚀 **Space Missions**       | Rolling 30-day launches with payload, stage, and recovery detail                                                                                                                                                                                                                                                                                                                    | Launch Library 2                        | 🟢 (🔴 optional paid token raises the allowance)                                                         |
+| 🚀 **Space Missions**       | Rolling 30-day launches with payload, stage, and recovery detail                                                                                                                                                                                                                                                                                                                    | Launch Library 2                        | 🟢 (🟡 optional token raises the allowance)                                                         |
 | 🎖️ **Mapped Installations** | Viewport-bounded military-site context from community mapping — incomplete by nature, and labeled that way                                                                                                                                                                                                                                                                          | OpenStreetMap                           | 🟢                                                                                                  |
 | 🌬️ **Wind**                 | Animated 10 m forecast wind with an optional speed, temperature or pressure color field and a reading at map center                                                                                                                                                                                                                                                                 | NOAA GFS / ECMWF IFS                    | 🟢                                                                                                  |
 | 🌦️ **Observed Weather**     | Rain radar (contiguous US), Satellite clouds (GOES regional or global infrared, Clouds only or Full image) and Lightning density (Americas and Pacific) on one history timeline                                                                                                                                                                                                     | NOAA nowCOAST                           | 🟢                                                                                                  |
@@ -531,11 +527,9 @@ _What the TomTom key buys you: rush-hour density painted on the city — then di
 |     | Key                  | Why                                                           | Get it                                             |
 | --- | -------------------- | ------------------------------------------------------------- | -------------------------------------------------- |
 | 🟡  | **OpenSky**          | ✈️ More flight-polling credits (🟢 anonymous works without)   | [opensky-network.org](https://opensky-network.org) |
-| 🔴  | **Launch Library 2** | 🚀 Optional paid token for higher limits (🟢 no key needed for public access) | [thespacedevs.com/supportus](https://thespacedevs.com/supportus) |
+| 🟡  | **Launch Library 2** | 🚀 Higher space-missions request allowance (🟢 works without) | [thespacedevs.com](https://thespacedevs.com)       |
 
 Add these if you need higher polling allowances.
-Leave `LL2_API_TOKEN` blank for standard public access. LL2 tokens are optional
-paid Patreon upgrades for higher limits; there is no free API-key signup.
 
 `npm run doctor` reports Node/npm readiness, the primary provider routes, and
 where each configured provider was found without printing credential values.

SECURITY.md

@@ -73,7 +73,7 @@ The data proxies under `server/providers/` are written so the browser cannot tur
 - **Sanitized errors** — internal error details are not echoed back to clients.
 - **Coalesced OAuth refresh** and cached successful responses only (OpenSky).
 - **Redacted debug logging.** The voice debug log (`.gev-logs/`, gitignored) strips API keys, bearer tokens, client secrets, and image data URLs before writing.
-- **Cross-site gate on cost/log endpoints.** The cost-bearing (`/api/realtime/token`, `/api/openai/hud-summary`, `/api/google/nearby-places`, `/api/google/text-search`), quota-bearing (`/api/mapillary/*`, with a per-IP limit on tiles, and `/api/tomtom/*`, backed by its persistent daily tile budget) and log (`/api/realtime/debug-log`) endpoints refuse cross-site browser requests: a foreign or opaque `Origin`, a `Sec-Fetch-Site` other than `same-origin`/`none` (this is what blocks an `<img>`/navigation that carries no `Origin`), or any reverse-proxy/CDN forwarding header returns `403`. Non-browser loopback tools (the repo QA harnesses POST the token endpoint with no `Origin`) and the explicit `HOST=0.0.0.0` LAN opt-in keep working — the gate deliberately does not require a loopback remote address; that stricter requirement belongs only to the credential panel (`admitKeySetupRequest`). The Host check (`allowedHosts`, applied by `hostCheckPlugin` ahead of every route, since Vite's own check runs only after plugin middleware) rejects a rebinding `Host` before any handler runs, in every mode, and the gate is defense in depth behind it: the LAN opt-in keeps that check and accepts only IP addresses, `localhost` and names listed in `GEV_ALLOWED_HOSTS`. **Limit:** a name you list there is trusted like the app's own address, so list only names you control. The keyless terrain route (`/api/terrain/heights`) uses the same cross-site checks, minus the forwarding-header refusal: it guards only the per-client quota and point cache, not a key or a bill, and the map needs it to render behind a reverse proxy.
+- **Cross-site gate on cost/log endpoints.** The cost-bearing (`/api/realtime/token`, `/api/openai/hud-summary`, `/api/google/nearby-places`, `/api/google/text-search`), quota-bearing (`/api/mapillary/*`, with a per-IP limit on tiles, and `/api/tomtom/*`, backed by its persistent daily tile budget) and log (`/api/realtime/debug-log`) endpoints refuse cross-site browser requests: a foreign or opaque `Origin`, a `Sec-Fetch-Site` other than `same-origin`/`none` (this is what blocks an `<img>`/navigation that carries no `Origin`), or any reverse-proxy/CDN forwarding header returns `403`. Non-browser loopback tools (the repo QA harnesses POST the token endpoint with no `Origin`) and the explicit `HOST=0.0.0.0` LAN opt-in keep working — the gate deliberately does not require a loopback remote address; that stricter requirement belongs only to the credential panel (`admitKeySetupRequest`). The Host check (`allowedHosts`, applied by `hostCheckPlugin` ahead of every route, since Vite's own check runs only after plugin middleware) rejects a rebinding `Host` before any handler runs, in every mode, and the gate is defense in depth behind it: the LAN opt-in keeps that check and accepts only IP addresses, `localhost` and names listed in `GEV_ALLOWED_HOSTS`. **Limit:** a name you list there is trusted like the app's own address, so list only names you control.
 - **Full Content-Security-Policy.** The dev and preview servers send a real CSP (`script-src 'self' 'unsafe-eval' blob:` plus the YouTube, Facebook and X scripts the Nepal event's embedded media loads and the Maps JavaScript API that Street View runs on, with a matching `frame-src` for their players and posts: no inline script and no other script origin; `blob:` covers the object URLs Cesium's bundled workers bootstrap through in the built app), alongside the existing `X-Frame-Options: DENY` and `frame-ancestors 'none'`. `'unsafe-eval'` stays because Knockout, bundled inside Cesium's widgets package, resolves the global object with `eval` at load time and the globe does not initialize without it; styles permit `'unsafe-inline'` and Google Fonts because Vite's dev client injects `<style>` elements.
 
 Allowing `maps.googleapis.com` in `script-src` also trusts its JSONP endpoints, which can bypass the script allowlist if an HTML-injection bug exists; this is an accepted limitation of loading the Maps JavaScript API, alongside the existing `'unsafe-eval'` allowance.

changelog.d/1056-area-tool-breakdowns.md

@@ -1,12 +0,0 @@
-- `aircraft_in_area` and `vessels_in_area` take `group_by` and `stats`, so an
-  MCP client can ask which airlines, countries, aircraft types or ship types
-  dominate an area, or the average altitude or speed, over every match instead
-  of estimating from the returned rows. Airlines come from the ICAO designator
-  in each callsign (SWA1234 counts as SWA), so the breakdown works on feeds
-  that report no operator; operator and type are counted only where the feed
-  reports them. Ship types count by family, so AIS codes 70 to 79 are all
-  cargo; type 0 ("not available") and the reserved codes 100 to 255 count as
-  unknown. Altitude and speed stats cover airborne aircraft only, so parked
-  aircraft do not pull the means down. Every vessel answer, `find_vessel`
-  included, now reads AIS ship-type codes as their family and a destination
-  with no letters as unknown (quanticsoul4772, #1056).

changelog.d/1133-cctv-qa-terrain-drag-fixture.md

@@ -1,6 +0,0 @@
-- Make CCTV QA ground-sampling checks respect the active terrain regime and
-  frame the actual calibration gizmo for the drag regression, preserving the
-  photoreal completion floor and all drag invariants.
-- Measure the tracking arrival regression on the first visible frame within
-  250 ms, accounting for the 80 ms fleet cadence while rejecting a stale
-  first-visible orientation instead of retrying until it is correct.

changelog.d/1197-launch-library-provider-guidance.md

@@ -1,5 +0,0 @@
-- Share Launch Library request cache keys across installations refreshing in the
-  same UTC minute, identify the app to the provider, and explain that standard
-  space-missions access needs no key. Optional higher-rate LL2 tokens are paid
-  upgrades; existing local cache and server-only token handling are unchanged
-  (rudycelekli, #1197).

changelog.d/1199-launch-cache-provenance.md

@@ -1,3 +0,0 @@
-- Keep Space Missions marked STALE when Launch Library 2 falls back to cached
-  launch data, and return to NOMINAL after a fresh response without discarding
-  retained missions (rudycelekli, #1199).

changelog.d/1200-cctv-live-icon-color.md

@@ -1,5 +0,0 @@
-- Color CCTV cameras with a video feed violet. Cameras with an HLS, MP4 or
-  WebM feed were the same cyan as stills, so a DelDOT or Statens vegvesen
-  video camera could only be found by opening it. Stills stay cyan and the
-  active camera stays amber, and focus de-emphasis fades the violet the same
-  way (Danielslay86, #1200).

changelog.d/1201-cctv-stills-aspect.md

@@ -1,4 +0,0 @@
-- Draw CCTV stills at their source aspect on the monitor plane instead of
-  stretching them to the 16:9 canvas. Most DOT cameras publish 4:3 frames, so
-  every still was widened; they are now centered and pillarboxed on the dark
-  the placeholder already ends on (Danielslay86, #1201).

changelog.d/1220-openai-typed-send.md

@@ -1,3 +0,0 @@
-- Avoid starting or queuing a reply when the local channel rejects a typed OpenAI
-  command, while preserving an earlier accepted deferred input
-  (Manjunath, #1220).

changelog.d/1228-cctv-ontario-511-key.md

@@ -1,6 +0,0 @@
-- Load Ontario 511 cameras again. 511on.ca's camera endpoint now requires a
-  free developer key; set `ONTARIO_511_API_KEY` to enable the pack, which is
-  otherwise skipped with one log line saying where to get a key
-  (quanticsoul4772, #1228).
-- Refuse Ontario catalog redirects and keep credential-bearing URLs and provider
-  exception text out of failure logs; retain the Ontario licence attribution.

changelog.d/1233-tarktee-datex-catalog-hardening.md

@@ -1,5 +0,0 @@
-- Harden the Tarktee (Estonia) DATEX2 camera catalog fetches: refuse redirects,
-  abort pending siblings and cancel received or late response streams when either
-  request fails before headers or overflows the 4 MB
-  byte cap, retain the shared 30 s dual-XML fetch deadline, and deduplicate camera
-  IDs before per-pack prioritization (yaka0007, #1233).

changelog.d/1234-cctv-catalog-background-refresh.md

@@ -1,5 +0,0 @@
-- Serve the camera catalog while it refreshes. An expired catalog made every
-  camera request wait for the slowest pack to reload; it is now answered at
-  once while one background refresh runs, so only the first load waits. Estonia's
-  slow Tarktee feeds get 30 s instead of 15 s, so the pack no longer drops out
-  on about a third of loads (quanticsoul4772, #1234).

changelog.d/605-fl511-florida-cameras.md

@@ -1,9 +0,0 @@
-- Add FL511 (Florida DOT) traffic cameras as an opt-in CCTV source pack:
-  the statewide ArcGIS catalog, read a page at a time under a byte cap with
-  redirects refused, and frames pinned to FL511's two image hosts over HTTPS.
-  FL511's terms limit its content to individual, personal use, and any other
-  use (a public deployment included) needs FDOT's express written consent, so
-  the pack stays off unless `CCTV_FLORIDA_ENABLED=1`. Headings come from the
-  catalog's direction codes, and camera ids come from the image channel, since
-  the catalog's ID column repeats across regions. `CCTV_FLORIDA_MAX_SOURCES`
-  sets the cap (Danielslay86, #605).

changelog.d/686-terrain-heights-bounds.md

@@ -1,9 +0,0 @@
-- Bound what a caller can grow through `/api/terrain/heights`. Every distinct
-  5-decimal point was a permanent in-memory entry, a permanent line in an
-  uncapped `.gev-cache/terrain-heights.json`, and a live upstream call, with
-  nothing limiting the rate. The point cache now holds at most 50,000 entries
-  and evicts oldest-first, a cache file above
-  24 MB is not read back, and the route is limited to 90 requests/minute per
-  client (270 global). Evicting a point costs one refetch, never a wrong
-  answer, since terrain does not move. Ordinary use is unaffected: a full
-  `test:track` run drives 10 requests, peaking at 8/min (daikaginza, #686).

changelog.d/816-radio-owner-restoration.md

@@ -1,7 +0,0 @@
-- Close the compact Radio disclosure when an adaptive tactical right-rail
-  restore directly expands Context, before Space Missions can be covered.
-  A repeated Context-open request also clears stale disclosure state.
-  Real PanelChrome constructor wiring and the rail reflow path are covered
-  by focused regressions. Credits: kvnloo (#816), raysung-2026's original
-  #804 report, asturksever's review, and quanticsoul4772's independent
-  Windows diagnosis.

changelog.d/872-gemini-live-voice.md

@@ -1,4 +0,0 @@
-- Add optional Gemini Live voice to the standalone app, with a provider chooser,
-  server-held API key, microphone streaming, shared map actions and captions.
-  Switching providers ends the old conversation and preserves the input mode
-  (Manjunath, #872).

changelog.d/880-world-packet-boundary.md

@@ -1,6 +0,0 @@
-- Extract a reusable model-free World Packet from the existing voice
-  `get_current_view_state` owner without restoring disabled layers to the
-  model context. Keep the enabled-only payload, disabled-layer count, source
-  provenance, action result and view-state contract; read the layer roster once
-  per packet; voice retains the speech/card envelope at its own boundary.
-  Credits: original GEV voice/layer contributors and #880 implementation.

changelog.d/945-cctv-vegvesen-kartverket-heights.md

@@ -1,17 +0,0 @@
-- Give each Statens vegvesen camera its own ground height from Kartverket's
-  keyless point-height API (CC BY 4.0) instead of one flat 150 m prior, so
-  mountain-pass cameras no longer sit hundreds of metres below the terrain
-  where neither the point-height prior nor the ground snap resolves. About 850
-  of ~855 cameras get a height; the rest keep the old prior. Requests carry 20
-  points, the most the API answers from its 1 m terrain model, eight at a
-  time; a cold lookup takes about 6–13 s. Cameras over water use the water
-  surface rather than the sea-floor depth the API returns there; for bridge
-  cameras that is still below the deck. Heights are cached for good and misses
-  for 6 h, so a refresh only asks about new or moved cameras. After a
-  failing request (a 408, 429 or 5xx, a network error, a request over 10 s or
-  an unreadable body) the lookup stops and backs off (Retry-After, else
-  30 min, longer than the refresh). The lane waits at most 12 s from its
-  start, and only on a cold cache; a slower first lookup leaves the cameras it
-  had not reached on the flat prior until the next 15-minute refresh, and
-  keeps filling the cache meanwhile.
-  `CCTV_VEGVESEN_HEIGHTS=0` turns it off. Follow-up to #929 (trygvehhh, #945).

changelog.d/975-terrain-cross-site-gate.md

@@ -1,8 +0,0 @@
-- Cross-site pages can no longer fill the terrain-height cache or spend the
-  visitor's own `/api/terrain/heights` rate-limit quota through the visitor's
-  browser. The route refuses a cross-site `Sec-Fetch-Site` or a foreign or
-  opaque `Origin` before rate limiting, cache access or upstream work. Unlike
-  the cost-bearing routes it still answers same-origin requests that arrive
-  through a reverse proxy, so terrain keeps rendering behind nginx, Caddy or
-  Cloudflare instead of falling back to the geoid (Sunil56224972, daikaginza,
-  #975).

docs/CURRENT-STATE.md

@@ -112,14 +112,7 @@ perimeters, terrain height, military installations and map features, plus a
 combined situation brief, military awareness around a point, the app's heads-up display caption, and a link that
 opens the app over an area. Tools reuse the layers' portable source factories, take a
 shared `area` argument (place name, bounding box, or point and radius) and cap
-lists at 25 rows by default. `aircraft_in_area` and `vessels_in_area` can also
+lists at 25 rows by default. Voice offers the same queries next to its app
-count every match by a field (`group_by`: airline, read from the ICAO
-designator in the callsign, or operator, country or type for aircraft; type or
-destination for ships; the ten largest groups, then other and unknown counts;
-the summary says when a feed reports none of the field) and summarize airborne
-altitude and speed (`stats`: count, min, median, mean, max).
-Both cover all matches, not just the rows returned; voice leaves these two
-tools out, so they reach MCP clients only. Voice offers the same queries next to its app
 actions: the session lists them, and the browser runs them through the same
 catalog, loaded on first use. See [tools and the MCP server](TOOLS.md).
 Aircraft altitude-band queries require a reported barometric or geometric altitude
@@ -496,11 +489,6 @@ to layer toggles, fly_to_location, frame_overhead, select_nearest_aircraft,
 get_entity_context, annotate_map and analyst_query. Analyst speech and the card
 share one deterministic count/scope headline; lower bounds use "At least" and
 partial answers name the unanswered layers. `get_current_view_state` lists enabled layers only.
-The model-free `gods-eye-view/agent/world-packet` export exposes
-`getWorldPacket({ viewer, styleManager, dataManager, sceneDirector })` to
-non-voice consumers. It reads the same enabled-only state and feed
-provenance before voice adds speech/card fields, with no new network requests
-or mutations.
 The voice card nested in the mic control (`voiceCard.js`) shows captions, plan
 steps and the result. `resultDisplay.js` is the one adapter from a result to
 the card: builder results show as built, and analyst results show a title
@@ -618,9 +606,7 @@ Reference feed construction is exported through `sources/reference`; the cable s
 
 Source factories have dedicated `layers/<family>/source` exports. ALPR and earthquake record normalization and CCTV source policy no longer pull rendering into source consumers. Catalog construction and voice feed reads use their focused owners; compatibility entries remain available. Settings filesystem hardening lives under `server/standalone/`. Import-direction checks complement export ownership checks; source behavior, settings policy and rendering are unchanged.
 
-Voice controls bind to a protocol-independent session factory. The default WebRTC adapter preserves the existing Realtime connection, push-to-talk, cost controls and radio handoff. Session subscriptions expose state, transcript, action call/progress/result, interruption, completion and turn-metrics events; stopping or replacing a session cancels pending actions. An active session's normal Stop publishes one idle transition, including adapters that emit their own terminal state; a restart triggered by that transition keeps ownership of its new startup state. Alternate adapters can use the same controls and action runner.
+Voice controls bind to a protocol-independent session factory. The default WebRTC adapter preserves the existing Realtime connection, push-to-talk, cost controls and radio handoff. Session subscriptions expose state, transcript, action call/progress/result, interruption, completion and turn-metrics events; stopping or replacing a session cancels pending actions. Alternate adapters can use the same controls and action runner.
-
-The standalone app offers OpenAI and Gemini Live through an explicit provider chooser. Gemini keeps its permanent API key on the local server and mints a short-lived, single-use credential with server-owned instructions and the standalone action catalog. Its native WebSocket adapter supports open microphone and push-to-talk input, streaming audio, captions and the existing action runner. In push-to-talk, a tool call that arrives with no input, reply or tool result outstanding is answered with a failure and never runs, and neither does any other call in the reply it starts; open-microphone turns start on Gemini's server-side activity detection, which reports no boundary to check. Switching providers ends the old conversation and releases its microphone and connection; only the input mode carries over. Gemini uses bounded shutdown draining and explicit manual restart, without automatic reconnection or a promise of uninterrupted session duration. Hosts that do not opt into the provider facade retain their existing default or custom adapter.
 
 Voice action argument schemas have one portable owner under `src/voice/actionSchemas.js`. The Realtime provider builds 30 tools using separate description-only metadata. Description customization cannot replace argument types, enum values or required fields.
 
@@ -826,11 +812,7 @@ position stay off the map. Genuine zero coordinates remain valid. Undisclosed
 stage coordinates, downrange distance and flight numbers remain unknown; the
 mission panel omits the flight-number label when no number was reported.
 Pending mission requests abort on disable/destruction and malformed launch
-snapshots preserve the last accepted display. A Launch Library stale-cache fallback
+snapshots preserve the last accepted display. Catalog groups, propagation cadence,
-retains its missions but reports STALE in Data Layers; a fresh snapshot clears that
-provenance. Hiding retained missions does not relabel them as fresh, and teardown
-clears the instance state. Injected getLaunches-only sources remain supported.
-Catalog groups, propagation cadence,
 tracking intent, replay timing, controls and source attribution remain unchanged.
 
 The fire layer now exposes `./layers/firms`: an instance factory with separate
@@ -1210,10 +1192,6 @@ Automatic collapse remains presentation only, prioritizes the latest explicit
 panel, and honors keyboard focus on the right. Mobile layout still releases
 desktop allocation styles. Stable Display allocation avoids unnecessary style
 writes. This extraction does not change panel positions or layout defaults.
-Context expansion through the panel owner or adaptive right-rail restoration
-closes an open compact Radio disclosure before Context/Space Missions becomes
-visible. The mini remains available while Context is collapsed. This fixes the
-Radio-overlap path reported in #804 without changing z-index or layout policy.
 The right rail skips panels hidden by other CSS (computed `display: none`), but
 keeps the collapsed panels its own exclusive presentation hides, so automatic
 collapse can still be undone.
@@ -1463,18 +1441,6 @@ an empty dock. Explicit zero and caller-supplied numeric fallbacks remain valid.
 
 ## Terrain height cache bound
 
-The `/api/terrain/heights` route refuses cross-site browser requests before
-rate limiting, cache access or upstream work: a `Sec-Fetch-Site` other than
-`same-origin`/`none` (an `<img>` on another page), or a foreign or opaque
-`Origin`, gets `403`. The per-client limiter keys on the socket address, which
-for such a request is the visitor's own browser, so without the gate any page
-could spend the visitor's 90/min quota and leave the app's own lookups on
-`429`. Unlike the cost-bearing routes, the terrain gate does not refuse
-reverse-proxy forwarding headers: terrain is keyless and needed for rendering,
-and a `403` there would send every chunk to the geoid fallback for an instance
-served behind the documented reverse proxy. Same-origin app requests,
-non-browser local callers and proxied same-origin requests keep working.
-
 The terrain proxy parser rejects finite longitudes outside [-180, 180] and
 latitudes outside [-90, 90] for every client before upstream resolution. One
 out-of-range point rejects the whole batch; inclusive WGS84 bounds remain valid.
@@ -1512,14 +1478,6 @@ The Node-only `gods-eye-view/server/providers/space` export supplies factories;
 `sources/space` supplies fixed upstream URL builders with no I/O or environment
 access. Callers retain validation, transport and response policy.
 
-LL2 recent-launch requests use UTC minute-aligned bounds over the same 30-day
-window, so installations refreshing in the same minute share an upstream cache
-key. The upper bound trails the current time by less than one minute. Requests
-identify the app and repository through User-Agent; the existing 15-minute local
-cache, stale fallback and optional server-only Authorization remain unchanged.
-Provider Settings identifies LL2 tokens as optional paid higher-rate upgrades:
-standard public access needs no key, and its field can remain blank.
-
 The shared TLE text parser skips incomplete named sets and resumes at the next
 complete set. A missing orbital line does not discard the later satellites in
 the catalog. A set whose two lines carry different catalog numbers, or a
@@ -2706,17 +2664,6 @@ down | auth-failed` (plus the unchanged `missing-key`/`unsupported`) with
 >   tunings. Ambient overlap includes each sprite's own rendered extent. The
 >   gated AIS, CCTV, and satellite passes retain an active-emphasis count so a
 >   settled dim contact always completes its release after tracking ends.
-> - **Terrain-height bounds:** because every distinct 5-decimal point is its own
->   cache key, its own line in `.gev-cache/terrain-heights.json`, and its own
->   upstream call, four limits bound what a caller can grow. Coordinates outside
->   WGS-84 range are rejected with `400` at parse (finite is not the same as on
->   Earth); the point cache holds at most 50,000 entries, evicting oldest-first
->   — terrain does not move, so an evicted point costs one refetch and never a
->   wrong answer; a cache file above 24 MB is not read back into memory (the
->   ceiling `rocketLaunchesProxy` already applies); and the route carries an
->   always-on limiter of 90 requests/minute/client, 270 global. That cap is an
->   order of magnitude above measured demand — a full `npm run test:track` run
->   drove 10 requests, peaking at 8/min.
 > - **Terrain-height resilience:** `/api/terrain/heights` caches canonical
 >   5-decimal points individually, reconstructs reordered/overlapping batches
 >   in exact request order, and refreshes only missing or stale points. Upstream
@@ -3448,7 +3395,7 @@ its criteria cannot be silently ignored.
 | Satellites             | CelesTrak                                                                                                                                                                                       | `src/data/satellites.js`                              | `/api/celestrak`                                         | 120s                                                                              |
 | Space Missions (30d)   | Launch Library 2 + CelesTrak                                                                                                                                                                    | `src/data/rocketLaunches.js`                          | `/api/launches` + `/api/celestrak/active`                | 5 min                                                                             |
 | Traffic | Selectable TomTom / OpenStreetMap / Hybrid roads; optional TomTom flow (BYOK) | `src/data/traffic.js` | browser-direct OpenFreeMap tiles; `/api/tomtom` for flow | viewport-driven; capped tile cache |
-| CCTV                   | Austin + Caltrans (CA) + TfL London + Ontario 511 + Fintraffic (FI) + DriveBC (BC) + TxDOT (TX) + Estonia (Tallinn, Tarktee) + Live Traffic NSW + Open Calgary Open Data + Statens vegvesen (NO, stills + live HLS, Kartverket ground heights) + King County (WA) Open Data + WSDOT (WA) Open Data + NYC DOT TMC (opt-in) + City of Toronto RESCU + Catalonia (Servei Català de Trànsit) + FL511 (FL, opt-in) + Street View fallback | `src/data/cctv.js`                                    | `/api/cctv`                                              | 10s (active)                                                                      |
+| CCTV                   | Austin + Caltrans (CA) + TfL London + Ontario 511 + Fintraffic (FI) + DriveBC (BC) + TxDOT (TX) + Estonia (Tallinn, Tarktee) + Live Traffic NSW + Open Calgary Open Data + Statens vegvesen (NO, stills + live HLS) + King County (WA) Open Data + WSDOT (WA) Open Data + NYC DOT TMC (opt-in) + City of Toronto RESCU + Catalonia (Servei Català de Trànsit) + Street View fallback | `src/data/cctv.js`                                    | `/api/cctv`                                              | 10s (active)                                                                      |
 | Radio                  | Radio Browser (public-domain station directory)                                                                                                                                                 | `src/data/radio.js`                                   | `/api/radio/stations`, `/api/radio/click/:uuid`          | 45 min directory refresh                                                          |
 | Transit 🚌             | Operator GTFS-Realtime VehiclePositions (7 keyless regions, `src/data/transitFeeds.js`)                                                                                                         | `src/layers/transit/` via `src/app/layers/transit.js` | `/api/transit`                                           | 15s (poll + delayed playback)                                                     |
 | Bikeshare 🚲           | GBFS (Lyft + BCycle + Social Bicycles + PBSC incl. Bike Share Toronto, Bike Itaú (Brazil), Bicing (Barcelona) and seven other Spanish cities + Urban Sharing, Entur, JCDecaux (Lillestrøm, Valencia, Seville) + nextbike (AMBici))                                                                                                                                        | `src/data/bikeshare.js`                               | `/api/gbfs`                                              | 60s                                                                               |
@@ -4419,7 +4366,7 @@ silently demoting every later lookup for the session.
 - **FIRMS**: no ground clamping (zero 3D-tiles height sampling), ≤18 screen-decluttered ambient labels, click-to-inspect detail card, 2.5k/3k sprite budgets viewport-clipped by FRP.
 - **CCTV v2 foundation:** a pitched
   frustum wireframe (4 corner rays + far-cap rectangle) with a monitor plane at the frustum's
-  far cap, retargeting the existing video/canvas texture pipeline. Stills are drawn at their source aspect, centered on the placeholder dark (`#01070c`), instead of being stretched to the 16:9 canvas. Manual calibration only —
+  far cap, retargeting the existing video/canvas texture pipeline. Manual calibration only —
   auto-calibration and the drape mesh pipeline are deleted. A one-shot activation obstruction
   probe (`pickFromRay` on camera activation, clamping the plane short of the first hit) remains;
   ground placement is superseded by the shared-floor v3 behavior below. Calibration persists to
@@ -4437,38 +4384,20 @@ silently demoting every later lookup for the session.
   ground clamp now lifts the cap _center_ only so the wireframe stays a true pyramid welded to
   the plane (was a flattened fan / the ~47.5 m divergence — RESOLVED), re-selecting the active
   camera is a no-op (killed a click-flash), and texture swaps gate on canvas content (killed a
-  periodic white flash). Camera icons are cyan for stills, violet for cameras with a video feed, and amber for the active camera. Coverage is now **metro-wide: 250 cameras** (`CCTV_AUSTIN_MAX_SOURCES`
+  periodic white flash). Coverage is now **metro-wide: 250 cameras** (`CCTV_AUSTIN_MAX_SOURCES`
   default 36 → 250, hard bound 300), filtered to `camera_status === TURNED_ON` (~815 live of
   1,003 rows). City packs (2026-07-04): Caltrans (districts 4/7/11/3 — SF, LA, San Diego,
   Sacramento; cap 300) and TfL London JamCams (cap 250) join Austin (cap 250) as keyless default
-  sources. Ontario 511 (2026-09-12) adds highway cameras including Kitchener-area routes
+  sources. Ontario 511 (2026-09-12) adds keyless highway cameras including Kitchener-area routes
-  (cap 1,000, all enabled rows from the current ~944-camera catalog). The 511on.ca API now
+  (cap 1,000, all enabled rows from the current ~944-camera catalog). All sources are RAW PRIOR
-  requires a developer key, so the pack needs `ONTARIO_511_API_KEY` and is skipped without one
-  (#1228). All sources are RAW PRIOR
   poses, and the layer is stills-first.
-  Fintraffic Finland road weather cameras (2026-09-13; cap 300, `CCTV_FINTRAFFIC_MAX_SOURCES`,
+  sources. Fintraffic Finland road weather cameras (2026-09-13; cap 300, `CCTV_FINTRAFFIC_MAX_SOURCES`,
   kill switch `CCTV_FINTRAFFIC_ENABLED=0`) are the fourth pack: one keyless GeoJSON station list
   covering the whole country, where one _preset_ (a station's fixed view) is one camera — 806
   GATHERING stations carry 2,256 in-collection presets, prioritized to 300 against seven anchors
   on the main road spine. `CCTV_MAX_SOURCES` is a 4,000 catalog-wide ceiling shared round-robin
   across packs, so a lower global cap thins every region instead of starving the last pack.
-  ~1,100 cameras total, all RAW PRIOR poses, stills-first. The catalog lives for 15 minutes; once
+  ~1,100 cameras total, all RAW PRIOR poses, stills-first.
-  it expires, `/api/cctv` keeps answering from it while one background refresh reloads every
-  pack, so only the very first load waits for the slowest pack (a live first load took about
-  22 s, and is bounded by Tarktee's 30 s). A background refresh that fails or comes back
-  empty keeps the old catalog and is retried after another 15 minutes, not on the next
-  request. Estonia's Tarktee DATEX feeds, which answer in 2 to 16.6 s, get 30 s
-  (`TARKTEE_FETCH_TIMEOUT_MS`) where other packs get 15 s.
-  Ontario catalog requests refuse redirects and log only a fixed diagnostic for
-  transport/JSON failures, so reflected request URLs or keys cannot reach logs.
-  Tarktee owns both XML requests with one 30-second deadline and shared abort;
-  a failed header or body read cancels its sibling, including a response arriving
-  after cleanup.
-  Both Tarktee XML catalogs refuse redirects and have a 4 MiB per-document
-  limit, enforced against declared length and streamed bytes. A rejected fetch,
-  unsuccessful response, or body-read failure releases both available response
-  bodies; read failures also cancel an active sibling reader. Cameras sharing
-  an image number are deduplicated before the Tarktee pack cap is applied.
 - **CCTV v3 UX — viewshed + calibration gizmo** (built 2026-07-05 and field
   validated 2026-07-21): the COVERAGE toggle is a
   tri-state cycle `OFF → ON → VIEWSHED`; viewshed mode renders each visible camera's frustum
@@ -4785,7 +4714,7 @@ and unreachable upstream (502/504) separately from road geometry.
   - **Every selectable layer writes that one slot** (2026-08-21). The tracking layers — flights, military, satellites — publish selection on their own awareness lane (`gev:awareness-subject-selected`, consumed by the readout card and the Contacts panel) and for the life of the voice tools never wrote the shared slot, so `scope:'selected'` silently answered `in_view` with a contact plainly selected on screen. They now call `selectTrackedSubjectContext` / `refreshTrackedSubjectContext` / `clearTrackedSubjectContext` (`src/data/contextStore.js`) on select / poll / deselect. **Invariants: (a)** that write path must NOT dispatch `gev:entity-selected` — tracking layers already own an event lane and a second one makes two surfaces fight over one subject; **(b)** exactly one record per tracking layer, because a frozen snapshot of a moved contact must never reach the visible-entity scan; **(c)** precedence is recency, not layer — one slot, last selection wins, so clicking an overlay entity supersedes a tracked plane as the voice subject while the plane stays tracked. Satellites refresh on the 1 s propagation beat, not per frame.
   - **Context-mode vocabulary is symmetric** (2026-08-21). `set_context_mode` accepts `contacts`; the internal id is `flights`. Every model-readable field (`mode`, `entering`, `priorMode`, nested `context`/`contextRollback`, and the transition diagnostic text) is reported in the accepted vocabulary, with the internal id preserved as `<field>Internal`; an absent secondary mode stays `null` rather than claiming to be `off`. Mapping lives in `src/contextModePolicy.js` so UI text and voice payloads cannot drift. Reporting the internal id made the model read `mode:'flights'` as "Contacts is off" and refuse to answer from the `contactsWindow` counts in the same payload.
   - **Analyst → track handoff carries a key, not just a label** (2026-08-21). `analyst_query` items include `icao24`/`mmsi` alongside the display `id`, and contact lookup uses the shared tiered ranking in `src/data/contactMatch.js`: hex exact → callsign exact → registration exact → callsign prefix → registration prefix → callsign substring → registration substring. The tiers keep an exact callsign ahead of a colliding registration regardless of feed order, and registrations compare separator-insensitively (`G-ABCD`/`GABCD`, `05-8152`/`058152`, `N123AB`/`N-123AB`).
-  - **A typed command supersedes the turn it interrupts** (2026-08-21; hardened 2026-10-17). `sendTextCommand` defers its `response.create` behind an active response instead of colliding with it, marks that response superseded so a late function call from it is refused rather than dispatched, and drops the old turn's queued follow-up. A refused call is still ANSWERED — a terminal `{ok:false, superseded:true}` `function_call_output` — because an unanswered `function_call` strands a pending call and deadlocks the model; the refusal creates no response of its own. A burst of typed commands coalesces into one response while keeping both conversation items. If the local channel rejects the user item, that command requests no response and adds no deferred answer; earlier accepted deferred input remains queued. Interruption and pointer preparation still happen before the send attempt.
+  - **A typed command supersedes the turn it interrupts** (2026-08-21). `sendTextCommand` defers its `response.create` behind an active response instead of colliding with it, marks that response superseded so a late function call from it is refused rather than dispatched, and drops the old turn's queued follow-up. A refused call is still ANSWERED — a terminal `{ok:false, superseded:true}` `function_call_output` — because an unanswered `function_call` strands a pending call and deadlocks the model; the refusal creates no response of its own. A burst of typed commands coalesces into one response while keeping both conversation items.
   - **Subject reconciliation across satellite catalog rebuilds** (2026-08-21). A dense↔core toggle or TLE refresh clears and repopulates the catalog, so the published subject is re-resolved against the new satrec; a subject that did NOT survive releases the slot. The per-frame refresh cannot do this itself — `_getTrackedFramePosition` returns early once the satellite has no catalog entry — so the reconcile runs at rebuild completion. An empty catalog is a rebuild in flight, not a disappearance.
   - **One aircraft-proximity snapshot** (2026-08-22; hardened 2026-09-30). `collectAircraftProximityWindow` (`src/data/militaryAwareness.js`) computes the Contacts panel cohort once. The voice analyst reads the exact retained snapshot and evaluation timestamp instead of re-scanning live layers, so the panel readout and spoken count for one centre cannot cross snapshots. **Invariant: do not re-derive a proximity count anywhere else.** Each layer retains 20,000 rows and samples one row beyond the cap; a saturated cohort reports `complete:false`, `truncated:true`, and is spoken as a lower bound. They diverged before because the panel read live billboard positions while the analyst used last-fix coordinates over a 2,000-record slice — 111 on screen, 15 spoken. Explicit regions, arbitrary points, and a radius different from the panel radius deliberately keep the general record engine. Entity-centred results carry `window: {engine:'contacts-window', centeredOn, radiusKm, flights, military, aircraft, complete, evaluatedAt}`.
   - **Centre precedence for nearby asks**: explicit place in the question > Contacts subject (a selected non-contact entity never silently becomes the centre) > an entity the user names > the current view, said aloud. Contacts active with no subject uses the view rather than reading an empty panel.

docs/TOOLS.md

@@ -263,11 +263,11 @@ and the development server's internal routes. See SECURITY.md.
 | `get_earthquakes`     | `earthquakes` | USGS M2.5+ events in the last 24 hours, strongest first        |
 | `get_active_fires`    | `fires`       | NASA FIRMS detections in an area, highest radiative power first |
 | `get_recent_launches` | `launches`    | Launch Library 2 launches in the last 30 days, newest first    |
-| `aircraft_in_area`    | `aircraft`    | Aircraft in an area, nearest first; `military: true` reads the `military` feed; `group_by` and `stats` count and summarize every match |
+| `aircraft_in_area`    | `aircraft`    | Aircraft in an area, nearest first; `military: true` reads the `military` feed |
 | `find_aircraft`       | `aircraft`    | Aircraft anywhere by callsign, ICAO address or registration    |
 | `get_aircraft_track`  | `aircraft`    | Recent positions of one aircraft, thinned to 200 points        |
 | `get_aircraft_info`   | `aircraft`    | Aircraft type and registration, and flight route, from adsbdb  |
-| `vessels_in_area` | `vessels` | Ships reported by AIS in an area, nearest first, optionally by type; `group_by` and `stats` count and summarize every match |
+| `vessels_in_area` | `vessels` | Ships reported by AIS in an area, nearest first, optionally by type |
 | `find_vessel` | `vessels` | Ships anywhere by MMSI, IMO number or name |
 | `get_vessel_track` | `vessels` | Recent positions of one ship, thinned to 200 points |
 | `next_satellite_pass` | `satellites` | Next pass over a place or point (default the ISS), with naked-eye visibility |

intro-sequence/.gitignore

@@ -0,0 +1,22 @@
+# Fetched snapshots and renders are regenerated by tools/; imagery and camera
+# stills carry third-party terms and are not redistributed with the repo.
+node_modules/
+/out/
+data/*.json
+data/*.txt
+!data/SOURCES.md
+/imagery/
+/cctv/
+audio/*.wav
+tools/imagery/cache/
+__pycache__/
+
+# fetch caches
+tools/*/cache/
+# city snapshots (Esri imagery, live feeds) and review/model artefacts
+/city/
+tools/flurry/review/
+tools/flurry/*.jpg
+tools/live/models/
+tools/live/*.jpg
+tools/*/check*.png

intro-sequence/README.md

@@ -0,0 +1,58 @@
+# God's Eye View — First Light
+
+The intro sequence: God's Eye View coming online for the first time. A seed of
+light on Null Island grows into a culture that turns out to be drawing the
+planet. It then indexes the surface tile by tile, ingests every public feed,
+and outgrows the dish it was grown in.
+
+Every number on screen comes from a real snapshot: 5,550 aircraft from OpenSky,
+15,928 satellites from CelesTrak, 246,411 fire detections from FIRMS, 10,120
+quakes from USGS, GFS wind, 1,948 subsea cable segments, AIS from Kystverket and
+Digitraffic, and 117 real public camera frames. Those cameras come from a
+catalog of 16,607 across 18 keyless agencies. The imagery is Esri World Imagery
+and NASA GIBS, fetched keyless. The score is synthesised from scratch and
+frame-locked to the same clock as the picture.
+
+## Acts
+
+| Time | Act | What happens |
+|---|---|---|
+| 0–5 s | Void | Boot console types, then implodes into a point |
+| 5–16 s | Seed / culture | Heartbeat, petri-dish ring. Mycelium grows out from 0°N 0°E; real night lights and coastlines light up as the front passes; the culture learns city names |
+| 16–30 s | Indexing | Quadtree tiles z3→z5 index in with rising resolution; the sun model is applied; 24 synthetic Esri captures ("enhance" z13→z18); full-frame Sobel feature extraction over Midtown |
+| 30–52 s | Ingestion | Aircraft, vessels, military, satellites, quakes, fires, wind and cloud, subsea cables, public cameras. Each feed has its own visual and sonic signature. Ends on the camera wall |
+| 52–60 s | Saturation | Every layer at once, data arcs, the digital-twin lattice, and the dish ring's return; containment falls, the ring shatters, OMNIPRESENT |
+| 61–72 s | Resolve | The planet becomes the iris of the logo. GOD'S EYE VIEW · NO PLACE LEFT BEHIND · ONLINE |
+
+## Rebuild
+
+```sh
+npm install                                # three, playwright-core, satellite.js, fonts
+python3 -m http.server 8765 --bind 127.0.0.1 &
+# data + imagery snapshots (see data/SOURCES.md)
+bash tools/fetch/fetch_basic.sh            # plus the other scripts in tools/fetch, tools/imagery
+node tools/export-cues.mjs                 # film clock -> audio/cues.json
+tools/render-all.sh 1920 1080 16x9         # deterministic frames -> out/video_16x9.mp4
+tools/render-all.sh 1080 1920 9x16
+tools/finalize.sh                          # score, -14 LUFS, mux -> out/final/
+```
+
+Single stills for review:
+`node tools/render.mjs --w 1920 --h 1080 --frames 12s,30s,58.4s --out out/stills`
+
+## Real-time / loading screen
+
+`index.html?play` runs the same frames live in a GPU browser, driven by the audio
+clock (the first click starts the sound). `?w=1080&h=1920&play` gives the
+vertical cut.
+
+## Layout
+
+- `src/timeline.js`: the clock. Every visual and audio event keys off it.
+- `src/main.js`: asset loading, camera choreography, per-frame state.
+- `src/globe.js`: planet shader (substrate → growth → quadtree indexing → lit Earth), clouds, atmosphere.
+- `src/lines.js`: coastline and mycelium growth fronts, cables, arcs, twin lattice.
+- `src/layers.js`: aircraft, vessels, satellites, quakes, fires, wind particles, stars.
+- `src/hud.js`: all typography and 2D: boot console, dish, captures, feed stack, camera wall, title.
+- `src/post.js`: HDR composite, dual-filter bloom, lens, grain, glitch.
+- `audio/score.py`: procedural score and sound design.

intro-sequence/audio/score.py

@@ -0,0 +1,679 @@
+#!/usr/bin/env python3
+"""God's Eye View — First Light: procedural score and sound design.
+
+Everything here is synthesised from scratch (no samples) and placed against
+audio/cues.json, which tools/export-cues.mjs exports from src/timeline.js, so
+every hit lands on its frame.
+
+    python3 audio/score.py            -> audio/score.wav (48 kHz, 24-bit stereo)
+"""
+import json
+import os
+import numpy as np
+from scipy import signal
+from scipy.io import wavfile
+
+SR = 48000
+HERE = os.path.dirname(os.path.abspath(__file__))
+C = json.load(open(os.path.join(HERE, 'cues.json')))
+T = C['T']
+DUR = C['DURATION']
+N = int(SR * DUR)
+rng = np.random.default_rng(20261018)
+
+# ---------------------------------------------------------------- buses
+def bus():
+    return np.zeros((2, N), dtype=np.float64)
+
+B = {k: bus() for k in ('drone', 'music', 'perc', 'hits', 'sfx', 'ui', 'verb')}
+
+
+def place(dst, sig, t, gain=1.0, pan=0.0, verb=0.0):
+    """Mix mono/stereo `sig` into bus `dst` at time t (s), equal-power pan."""
+    if sig.ndim == 1:
+        p = (pan + 1) * np.pi / 4
+        sig = np.vstack([sig * np.cos(p), sig * np.sin(p)])
+    i0 = int(round(t * SR))
+    if i0 >= N:
+        return
+    s0 = max(0, -i0)
+    i0 = max(0, i0)
+    n = min(sig.shape[1] - s0, N - i0)
+    if n <= 0:
+        return
+    seg = sig[:, s0:s0 + n] * gain
+    B[dst][:, i0:i0 + n] += seg
+    if verb > 0:
+        B['verb'][:, i0:i0 + n] += seg * verb
+
+
+def tt(dur):
+    return np.arange(int(dur * SR)) / SR
+
+
+def note(name):
+    names = {'C': -9, 'C#': -8, 'Db': -8, 'D': -7, 'D#': -6, 'Eb': -6, 'E': -5, 'F': -4, 'F#': -3, 'Gb': -3, 'G': -2, 'G#': -1, 'Ab': -1, 'A': 0, 'A#': 1, 'Bb': 1, 'B': 2}
+    n, o = name[:-1], int(name[-1])
+    return 440.0 * 2 ** ((names[n] + (o - 4) * 12) / 12)
+
+
+def sos_lp(fc, order=2):
+    return signal.butter(order, min(fc, SR * 0.45), 'low', fs=SR, output='sos')
+
+
+def sos_hp(fc, order=2):
+    return signal.butter(order, max(fc, 10), 'high', fs=SR, output='sos')
+
+
+def sos_bp(lo, hi, order=2):
+    return signal.butter(order, [max(lo, 10), min(hi, SR * 0.45)], 'band', fs=SR, output='sos')
+
+
+def filt(x, sos):
+    return signal.sosfilt(sos, x, axis=-1)
+
+
+def sweep_filter(x, cut_fn, kind='low', block=256, order=2):
+    """Time-varying Butterworth: coefficients per block, state carried across."""
+    y = np.zeros_like(x)
+    zi = None
+    for b in range(0, len(x), block):
+        tc = b / SR
+        fc = float(cut_fn(tc))
+        if kind == 'low':
+            sos = sos_lp(fc, order)
+        elif kind == 'high':
+            sos = sos_hp(fc, order)
+        else:
+            bw = fc * 0.35
+            sos = sos_bp(fc - bw, fc + bw, order)
+        if zi is None:
+            zi = signal.sosfilt_zi(sos) * 0
+        y[b:b + block], zi = signal.sosfilt(sos, x[b:b + block], zi=zi)
+    return y
+
+
+def saw(f, dur, phase=0.0):
+    t = tt(dur)
+    if np.isscalar(f):
+        ph = f * t + phase
+    else:
+        ph = np.cumsum(f) / SR + phase
+    return 2 * (ph - np.floor(ph + 0.5))
+
+
+def sine(f, dur, phase=0.0):
+    t = tt(dur)
+    if np.isscalar(f):
+        return np.sin(2 * np.pi * f * t + phase)
+    return np.sin(2 * np.pi * np.cumsum(f) / SR + phase)
+
+
+def noise(dur):
+    return rng.standard_normal(int(dur * SR))
+
+
+def env_exp(dur, decay, attack=0.002):
+    t = tt(dur)
+    a = np.minimum(1, t / max(attack, 1e-4))
+    return a * np.exp(-t * decay)
+
+
+def env_ar(dur, attack, release, curve=2.0):
+    t = tt(dur)
+    up = np.clip(t / max(attack, 1e-4), 0, 1) ** curve
+    down = np.clip((dur - t) / max(release, 1e-4), 0, 1) ** curve
+    return np.minimum(up, down)
+
+
+# ---------------------------------------------------------------- instruments
+def click(freq=4000, dur=0.012, q=0.5):
+    x = noise(dur) * env_exp(dur, 900, 0.0003)
+    return filt(x, sos_bp(freq * (1 - q * 0.5), freq * (1 + q)))
+
+
+def blip(f, dur=0.05, harm=0.25, decay=60):
+    t = tt(dur)
+    e = env_exp(dur, decay, 0.001)
+    return (np.sin(2 * np.pi * f * t) + harm * np.sin(4 * np.pi * f * t)) * e
+
+
+def thump(f0=70, f1=34, dur=0.9, decay=5.0, punch=24):
+    t = tt(dur)
+    f = f1 + (f0 - f1) * np.exp(-t * punch)
+    body = sine(f, dur) * env_exp(dur, decay, 0.001)
+    tr = filt(noise(0.02), sos_lp(2500)) * env_exp(0.02, 200)
+    out = body
+    out[: len(tr)] += tr * 0.4
+    return out
+
+
+def braam(dur=4.0, notes=('D1', 'A1', 'D2', 'A2'), bright=2600, gain=1.0, decay=1.6):
+    """Detuned saw stack through a fast-opening, slow-closing lowpass + drive."""
+    n = int(dur * SR)
+    acc = np.zeros(n)
+    for nm in notes:
+        f = note(nm)
+        for d in (-0.012, -0.005, 0.0, 0.006, 0.013):
+            acc += saw(f * (1 + d), dur, rng.random())
+    acc /= len(notes) * 3.0
+    cut = lambda tc: 160 + (bright - 160) * min(1.0, tc / 0.07) * np.exp(-max(0.0, tc - 0.07) * decay)
+    y = sweep_filter(acc, cut, 'low', order=2)
+    y = np.tanh(y * 2.2) * env_ar(dur, 0.012, dur * 0.85, 1.2)
+    sub = sine(note(notes[0]) * np.ones(n) * (1 + 0.5 * np.exp(-tt(dur) * 18)), dur) * env_exp(dur, 1.3, 0.004)
+    imp = filt(noise(0.6), sos_lp(900)) * env_exp(0.6, 9)
+    out = y * 0.85 + sub * 0.9
+    out[: len(imp)] += imp * 0.5
+    return out * gain
+
+
+def whoosh(dur=1.2, f0=400, f1=4000, peak=0.5):
+    x = noise(dur)
+    t0 = tt(dur)
+    cut = lambda tc: f0 * (f1 / f0) ** min(1.0, tc / dur)
+    y = sweep_filter(x, cut, 'band', order=2)
+    shape = np.exp(-((t0 / dur - peak) ** 2) / 0.05)
+    return y * shape
+
+
+def riser(dur=3.0, f0=200, f1=6000):
+    x = noise(dur)
+    cut = lambda tc: f0 * (f1 / f0) ** ((tc / dur) ** 1.6)
+    y = sweep_filter(x, cut, 'band', order=2)
+    t0 = tt(dur)
+    tone = sine(f0 * (f1 / f0 / 8) ** ((t0 / dur) ** 1.6) * np.ones_like(t0), dur) * 0.2
+    return (y + tone) * (t0 / dur) ** 2.2
+
+
+def shepard(dur, rate_oct_per_s, base=40.0, layers=9, accel=0.0):
+    t0 = tt(dur)
+    pos = rate_oct_per_s * t0 + 0.5 * accel * t0 ** 2
+    out = np.zeros_like(t0)
+    for k in range(layers):
+        o = (k + pos) % layers
+        f = base * 2 ** o
+        a = np.exp(-((o - layers / 2) ** 2) / (2 * (layers / 5) ** 2))
+        ph = np.cumsum(f) / SR
+        out += np.sin(2 * np.pi * ph) * a
+    return out / layers * 2
+
+
+def fm_bell(f, dur=2.0, ratio=3.5, index=4.0, decay=2.5):
+    t = tt(dur)
+    e = env_exp(dur, decay, 0.002)
+    mod = np.sin(2 * np.pi * f * ratio * t) * index * np.exp(-t * 3)
+    return np.sin(2 * np.pi * f * t + mod) * e
+
+
+def pluck(f, dur=0.22, cutoff=1800, decay=14):
+    x = saw(f, dur, rng.random()) + 0.5 * saw(f * 1.005, dur, rng.random())
+    e = env_exp(dur, decay, 0.002)
+    cut = lambda tc: 120 + cutoff * np.exp(-tc * 22)
+    return sweep_filter(x * e, cut, 'low', block=128, order=2) * 0.7
+
+
+def pad(freqs, dur, cutoff=900, attack=1.2, release=1.5):
+    n = int(dur * SR)
+    acc = np.zeros(n)
+    for f in freqs:
+        for d in (-0.004, 0.0, 0.0045):
+            acc += saw(f * (1 + d), dur, rng.random())
+    acc /= len(freqs) * 3
+    y = filt(acc, sos_lp(cutoff, 2))
+    return y * env_ar(dur, attack, release, 1.5)
+
+
+def static(dur, lo=1500, hi=9000):
+    return filt(noise(dur), sos_bp(lo, hi))
+
+
+def stereo_noise_bed(dur, lo, hi):
+    return np.vstack([filt(noise(dur), sos_bp(lo, hi)), filt(noise(dur), sos_bp(lo, hi))])
+
+
+# =================================================================== ACT 0
+# room tone that the whole film sits on
+bed = stereo_noise_bed(DUR, 30, 140) * 0.05
+ramp_bed = np.clip(tt(DUR) / 3.0, 0, 1)
+B['drone'] += bed * ramp_bed
+
+# sub drone: D1 + A1, breathing; intensity rises with the film, dies at the cut
+t_all = tt(DUR)
+intensity = np.interp(t_all, [0, 5, 9, 16, 30, 52, 60.4, 60.5, 61.2, 66, 72], [0.0, 0.25, 0.45, 0.6, 0.7, 0.85, 1.0, 0.0, 0.0, 0.7, 0.0])
+dr = (np.sin(2 * np.pi * note('D1') * t_all) * 0.6 + np.sin(2 * np.pi * note('A1') * 1.001 * t_all) * 0.25 + np.sin(2 * np.pi * note('D2') * 0.999 * t_all) * 0.18)
+dr *= 0.85 + 0.15 * np.sin(2 * np.pi * 0.11 * t_all)
+B['drone'] += np.vstack([dr, dr]) * intensity * 0.35
+
+# electrical hum under the boot console
+hum_e = np.interp(t_all, [0.4, 1.2, T['collapse'], T['seed']], [0, 1, 1, 0], left=0, right=0)
+hum = (sine(100, DUR) * 0.3 + sine(150, DUR) * 0.12 + filt(noise(DUR), sos_bp(90, 400)) * 0.05) * hum_e
+place('sfx', hum, 0, 0.18)
+
+# keystrokes
+for k in C['boot']:
+    if k['ch'] == ' ':
+        continue
+    f = 3500 + rng.random() * 2500
+    place('ui', click(f, 0.01), k['t'], 0.22 + rng.random() * 0.08, pan=(rng.random() - 0.5) * 0.3)
+# "OK" confirmation
+place('ui', blip(1760, 0.09) * 0.6 + blip(2640, 0.09) * 0.3, T['boot'] + 0.75 + 41 / 55, 0.25, verb=0.2)
+# cursor appears
+place('ui', blip(1200, 0.03), T['cursor'], 0.12)
+
+# collapse: suck-in riser then silence, then the seed ignites
+place('sfx', riser(T['seed'] - T['collapse'] + 0.05, 300, 9000)[::-1][::-1] * 1.0, T['collapse'], 0.35)
+rev = whoosh(0.6, 6000, 300, 0.85)
+place('sfx', rev, T['collapse'] - 0.15, 0.4)
+place('hits', thump(90, 32, 1.4, 3.5), T['seed'], 0.85, verb=0.3)
+place('ui', fm_bell(note('D6'), 2.5, 2.0, 1.5, 1.6), T['seed'], 0.16, verb=0.6)
+
+# heartbeat
+for bt, g in ((T['beat1'], 0.9), (T['beat2'], 1.0)):
+    place('hits', thump(62, 30, 0.7, 7.5, 30), bt, g * 1.4, verb=0.25)
+    place('hits', thump(52, 28, 0.6, 9, 30), bt + 0.19, g * 0.55, verb=0.2)
+
+# dish ticks: 120 ticks swept around the ring, panned with the sweep
+for i in range(120):
+    k = i / 120
+    # easeInOut timing of the sweep
+    u = np.interp(k, np.linspace(0, 1, 400), [((4 * x ** 3) if x < 0.5 else 1 - (-2 * x + 2) ** 3 / 2) for x in np.linspace(0, 1, 400)])
+    tk = T['dishDraw'] + u * (T['dishDone'] - T['dishDraw'])
+    loud = 0.12 if i % 10 == 0 else 0.05
+    place('ui', click(6500 if i % 10 else 3800, 0.008), tk, loud, pan=np.sin(k * 2 * np.pi) * 0.8)
+
+# =================================================================== ACT 1 growth
+gs, ge = T['growStart'], T['growEnd']
+# granular crackle, density following exponential growth
+for _ in range(2600):
+    x = rng.random() ** 0.45  # skewed late
+    tc = gs + x * (ge - gs + 0.3)
+    k = (np.exp(3 * (tc - gs) / (ge - gs)) - 1) / (np.exp(3) - 1)
+    if rng.random() > 0.15 + 0.85 * k:
+        continue
+    f = 1800 + rng.random() * 7000
+    place('sfx', click(f, 0.006 + rng.random() * 0.01, 0.8), tc, 0.05 + 0.1 * rng.random() * (0.4 + k), pan=rng.uniform(-0.9, 0.9))
+# organic tone: saw cluster gliding up an octave, filter opening
+dur = ge - gs + 0.6
+tg = tt(dur)
+glide = note('D2') * 2 ** (((tg / dur) ** 1.8))
+cl = (saw(glide, dur) + saw(glide * 1.007, dur) + saw(glide * 1.5, dur) * 0.4)
+cl = sweep_filter(cl, lambda tc: 150 + 2200 * (tc / dur) ** 2, 'low', order=2)
+cl *= env_ar(dur, 2.5, 0.35, 1.4) * 0.18
+place('music', cl, gs, 1.0, verb=0.25)
+# city pings as the culture learns names
+for i in range(30):
+    tc = 10.2 + (i / 30) ** 0.8 * 5.2 + rng.random() * 0.1
+    place('ui', blip(2000 + rng.choice([0, 300, 500, 700, 1000]), 0.06, 0.2, 45), tc, 0.08, pan=rng.uniform(-0.8, 0.8), verb=0.25)
+# reverse swell into the substrate hit
+place('sfx', riser(1.6, 120, 5000), T['substrate'] - 1.6, 0.3)
+
+# =================================================================== hits
+place('hits', braam(4.5, ('D1', 'A1', 'D2'), 1800, 1.0, 1.4), T['substrate'], 0.75, verb=0.35)
+
+# =================================================================== ACT 2 indexing
+BPM = 120.0
+beat = 60 / BPM
+s16 = beat / 4
+grid0 = 17.0
+
+pattern = ['D3', 'D3', 'F3', 'D3', 'A3', 'D3', 'C4', 'D3', 'D3', 'D3', 'F3', 'D3', 'G3', 'D3', 'A3', 'F3']
+prog = [('D', ['D3', 'F3', 'A3']), ('Bb', ['Bb2', 'D3', 'F3']), ('G', ['G2', 'Bb2', 'D3']), ('A', ['A2', 'C#3', 'E3'])]
+
+
+def ostinato(t0, t1, cutoff_fn, gain_fn, transpose=0, every=1):
+    i = 0
+    t = t0
+    while t < t1 - 1e-6:
+        if i % every == 0:
+            nm = pattern[i % 16]
+            bar = int((t - grid0) / (beat * 8)) % 4
+            f = note(nm) * 2 ** (transpose / 12)
+            # follow the chord root on bar changes
+            if prog[bar][0] == 'Bb' and nm == 'A3':
+                f = note('Bb3')
+            if prog[bar][0] == 'A' and nm == 'C4':
+                f = note('C#4')
+            acc = 1.0 if i % 4 == 0 else 0.7
+            place('music', pluck(f, 0.25, cutoff_fn(t)), t, gain_fn(t) * acc, pan=0.25 if i % 2 else -0.25, verb=0.12)
+        i += 1
+        t += s16
+
+
+ostinato(17.0, 29.9, lambda t: 500 + 2200 * ((t - 17) / 13) ** 1.5, lambda t: 0.06 + 0.1 * (t - 17) / 13)
+
+# pads under indexing
+for k, t0 in enumerate(np.arange(17.0, 30.0, 4.0)):
+    nm, ch = prog[k % 4]
+    place('music', pad([note(x) for x in ch], 4.3, 700 + k * 120, 1.0, 1.2), t0, 0.12, verb=0.3)
+
+# tile flips: a spray of pitched blips, hemisphere in view only
+scale = [note(x) for x in ('D6', 'F6', 'G6', 'A6', 'C7', 'D7')]
+for tl in C['tiles']:
+    if not tl['vis'] or tl['t'] > 26.5:
+        continue
+    z = tl['z']
+    if z == 5 and rng.random() > 0.35:
+        continue
+    f = scale[rng.integers(0, len(scale))] / (2 if z == 3 else 1) * (1 if z < 5 else 1.5)
+    g = {3: 0.07, 4: 0.04, 5: 0.025}[z]
+    place('ui', blip(f, 0.05, 0.1, 70), tl['t'], g, pan=tl['pan'] * 0.8, verb=0.1)
+    if z == 3:
+        place('ui', click(3000, 0.012), tl['t'], 0.06, pan=tl['pan'] * 0.8)
+
+
+def shutter(t, g=1.0, pan=0.3):
+    place('sfx', click(3800, 0.008, 0.6), t, 0.5 * g, pan)
+    place('sfx', click(2200, 0.014, 0.6), t + 0.045, 0.4 * g, pan)
+    place('sfx', thump(160, 90, 0.05, 60, 80), t, 0.15 * g, pan)
+    place('ui', blip(2637, 0.05, 0.1, 60), t + 0.07, 0.12 * g, pan)
+
+
+for cp in C['caps']:
+    if cp['slow']:
+        t0 = cp['t']
+        shutter(t0, 1.0, -0.35)
+        # the enhance: rising sweep with data chatter
+        d = 1.05
+        tz = tt(d)
+        f = 300 * (8 ** ((tz / d) ** 1.5))
+        sw = sine(f, d) * 0.5 + sine(f * 1.5, d) * 0.15
+        sw *= env_ar(d, 0.1, 0.15) * (0.7 + 0.3 * np.sin(2 * np.pi * 18 * tz))
+        place('sfx', sw, t0 + 0.28, 0.06, -0.3, verb=0.2)
+        for j in range(16):
+            place('ui', blip(1500 + rng.random() * 3000, 0.02, 0, 120), t0 + 0.3 + j * 0.06, 0.05, rng.uniform(-0.6, 0.2))
+        place('sfx', whoosh(0.5, 800, 5000, 0.5), t0 + 1.35, 0.18, 0.4)
+        place('ui', click(5000, 0.01), t0 + 1.75, 0.2, 0.6)
+    else:
+        shutter(cp['t'], 0.55, 0.6)
+
+# full-frame feature extraction
+cf = T['capFull']
+place('sfx', whoosh(0.7, 300, 3000, 0.4), cf, 0.3)
+place('hits', thump(80, 40, 0.8, 6), cf + 0.5, 0.35, verb=0.3)
+scan_d = 1.6
+ts = tt(scan_d)
+scan = (sine(220, scan_d) + 0.5 * sine(440 * (1 + 0.002 * np.sin(2 * np.pi * 6 * ts)), scan_d) + 0.3 * sine(1320, scan_d)) * env_ar(scan_d, 0.08, 0.2)
+scan *= 0.6 + 0.4 * np.sin(2 * np.pi * 12 * ts)
+place('sfx', scan, cf + 0.75, 0.07, 0, verb=0.2)
+for j in range(70):
+    place('ui', click(5000 + rng.random() * 3000, 0.006), cf + 0.75 + j * (1.6 / 70), 0.06, rng.uniform(-0.5, 0.5))
+# collapse into the planet
+place('sfx', riser(0.9, 300, 8000), T['indexed'] - 0.9, 0.4)
+place('sfx', whoosh(0.5, 6000, 200, 0.8), T['indexed'] - 0.45, 0.35)
+
+# SURFACE INDEXED
+place('hits', braam(5.0, ('D1', 'A1', 'D2', 'F2'), 2600, 1.0, 1.1), T['indexed'], 0.95, verb=0.4)
+
+# =================================================================== ACT 3 ingestion
+ostinato(30.5, 52.4, lambda t: 900 + 2600 * min(1, (t - 30.5) / 18), lambda t: 0.09 + 0.06 * (t - 30.5) / 22)
+# bass
+for k, t0 in enumerate(np.arange(30.5, 52.4, beat * 2)):
+    bar = int((t0 - grid0) / (beat * 8)) % 4
+    root = {'D': 'D1', 'Bb': 'Bb0', 'G': 'G1', 'A': 'A1'}[prog[bar][0]]
+    b = saw(note(root), 0.9) + saw(note(root) * 1.004, 0.9)
+    b = filt(b, sos_lp(260)) * env_exp(0.9, 3.5, 0.005)
+    place('music', b, t0, 0.22)
+for k, t0 in enumerate(np.arange(30.5, 52.4, 4.0)):
+    nm, ch = prog[k % 4]
+    place('music', pad([note(x) for x in ch] + [note(ch[0][:-1] + str(int(ch[0][-1]) + 1))], 4.3, 1100, 0.8, 1.2), t0, 0.12, verb=0.3)
+# percussion: low taiko-ish hits + ticks
+for i, t0 in enumerate(np.arange(30.5, 52.4, beat)):
+    if i % 4 in (0, 2) or (i % 8 == 7):
+        place('perc', thump(95, 45, 0.5, 9, 40), t0, 0.45 if i % 4 == 0 else 0.3, verb=0.12)
+    place('perc', click(9000, 0.02, 0.4), t0 + beat / 2, 0.06)
+    if i % 4 == 2:
+        sn = filt(noise(0.2), sos_bp(900, 4000)) * env_exp(0.2, 22) + sine(190, 0.2) * env_exp(0.2, 30) * 0.5
+        place('perc', sn, t0, 0.13, verb=0.25)
+
+
+def feed_sig(key, t):
+    """Each feed gets its own sonic signature as it comes online."""
+    place('ui', blip(1760, 0.06, 0.2, 40) + blip(2349, 0.06, 0.1, 40) * 0.6, t, 0.15, -0.5, verb=0.15)
+    place('ui', click(4500, 0.01), t, 0.25, -0.5)
+    if key == 'air':
+        for j in range(500):
+            x = rng.random() ** 0.7 * 1.9
+            place('ui', click(5000 + rng.random() * 4000, 0.004), t + x, 0.05 + rng.random() * 0.05, rng.uniform(-0.9, 0.9))
+        place('sfx', whoosh(1.4, 500, 7000, 0.35), t, 0.18, 0.3)
+    elif key == 'sea':
+        ping = sine(1150 * np.exp(-tt(2.2) * 0.05), 2.2) * env_exp(2.2, 2.2, 0.003)
+        place('sfx', ping, t + 0.05, 0.22, 0.2, verb=0.8)
+        place('sfx', ping, t + 1.05, 0.1, -0.3, verb=0.8)
+        place('sfx', filt(noise(2.0), sos_lp(400)) * env_ar(2.0, 0.5, 1.2), t, 0.2)
+    elif key == 'mil':
+        for j in range(3):
+            tone = (np.sign(np.sin(2 * np.pi * 740 * tt(0.12))) * 0.3 + sine(740, 0.12)) * env_ar(0.12, 0.005, 0.03)
+            place('ui', filt(tone, sos_lp(3000)), t + 0.1 + j * 0.22, 0.12, 0.3)
+            tone2 = (np.sign(np.sin(2 * np.pi * 554 * tt(0.12))) * 0.3 + sine(554, 0.12)) * env_ar(0.12, 0.005, 0.03)
+            place('ui', filt(tone2, sos_lp(3000)), t + 0.21 + j * 0.22, 0.1, 0.3)
+    elif key == 'orbit':
+        for j in range(26):
+            f = scale[rng.integers(0, len(scale))] * rng.choice([0.5, 1, 1])
+            place('music', fm_bell(f, 2.5, 3.5, 2.5, 2.2), t + rng.random() * 2.2, 0.035, rng.uniform(-0.9, 0.9), verb=0.6)
+        place('sfx', whoosh(2.8, 2500, 200, 0.4), t + 0.2, 0.3, 0)
+        place('hits', thump(60, 30, 1.6, 2.5), t + 0.1, 0.4, verb=0.3)
+    elif key == 'quake':
+        for j, dt in enumerate((0.05, 0.42, 0.95)):
+            place('hits', thump(55, 26, 1.4, 3.2, 18), t + dt, 0.6 - j * 0.12, rng.uniform(-0.5, 0.5), verb=0.25)
+        place('sfx', filt(noise(2.5), sos_lp(90)) * env_ar(2.5, 0.2, 1.8), t, 0.9)
+    elif key == 'fire':
+        d = 2.2
+        for j in range(900):
+            x = rng.random() ** 1.3 * d
+            g = (1 - x / d) * 0.12
+            place('sfx', click(800 + rng.random() * 5000, 0.004 + rng.random() * 0.01, 0.9), t + x, g * rng.random(), rng.uniform(-0.8, 0.8))
+        place('sfx', filt(noise(d), sos_bp(200, 1500)) * env_ar(d, 0.05, 1.6), t, 0.08)
+    elif key == 'wind':
+        d = 3.0
+        w = sweep_filter(noise(d), lambda tc: 250 + 900 * np.sin(np.pi * tc / d), 'band', order=2)
+        w2 = sweep_filter(noise(d), lambda tc: max(180, 300 + 700 * np.sin(np.pi * tc / d + 0.6)), 'band', order=2)
+        place('sfx', np.vstack([w, w2]) * env_ar(d, 0.6, 1.6), t, 0.4)
+    elif key == 'cable':
+        d = 1.8
+        buzz = filt(saw(60, d) + 0.5 * saw(120.5, d), sos_bp(300, 2500)) * env_ar(d, 0.02, 1.0)
+        gate = (np.sin(2 * np.pi * 7 * tt(d)) > 0.2).astype(float)
+        place('sfx', buzz * (0.4 + 0.6 * gate), t, 0.08, 0.2)
+        place('sfx', sine(3000 * np.exp(-tt(0.25) * 12) + 150, 0.25) * env_exp(0.25, 12), t, 0.1, -0.2)
+    elif key == 'cctv':
+        for j in range(9):
+            tc = t + 0.25 + j * 0.12
+            place('sfx', click(2500, 0.01), tc, 0.3, rng.uniform(-0.7, 0.7))
+            place('sfx', static(0.12) * env_exp(0.12, 25), tc, 0.05, rng.uniform(-0.7, 0.7))
+
+
+for fd in C['feeds']:
+    feed_sig(fd['key'], fd['t'])
+
+# camera moves
+place('sfx', whoosh(2.3, 200, 2500, 0.5), 33.6, 0.22, -0.4)
+place('sfx', whoosh(2.8, 2200, 180, 0.5), 37.2, 0.22, 0.4)
+place('sfx', whoosh(2.0, 300, 3000, 0.5), 40.4, 0.15, -0.2)
+
+# THE WALL
+wall_t = T['cctvWall']
+place('hits', braam(3.5, ('D1', 'A1', 'D2'), 1900, 0.9, 1.6), wall_t, 0.85, verb=0.3)
+for j in range(100):
+    tc = wall_t + (rng.random() ** 0.8) * 0.85 + rng.random() * 0.12
+    place('sfx', click(2000 + rng.random() * 2500, 0.012), tc, 0.18, rng.uniform(-0.95, 0.95))
+    place('sfx', static(0.08) * env_exp(0.08, 30), tc, 0.04, rng.uniform(-0.95, 0.95))
+wd = T['cctvOut'] - wall_t + 0.3
+wbed = stereo_noise_bed(wd, 800, 7000) * env_ar(wd, 0.4, 0.25)
+place('sfx', wbed, wall_t, 0.05)
+murmur = (sine(15625 / 2, wd) * 0.02 + filt(noise(wd), sos_bp(100, 300)) * 0.4) * env_ar(wd, 0.3, 0.2)
+place('sfx', murmur, wall_t, 0.12)
+# the watcher hopping cell to cell (7 Hz)
+for j in range(int((T['cctvOut'] - wall_t - 0.8) * 7)):
+    tc = wall_t + 0.8 + j / 7
+    place('ui', blip(3136, 0.025, 0.0, 90), tc, 0.06, rng.uniform(-0.8, 0.8))
+# rapid list
+for j, tc in enumerate(C['rapid']):
+    place('ui', blip(note('D6') * 2 ** (j / 12 * 2), 0.06, 0.2, 45), tc, 0.12, -0.5, verb=0.15)
+# collapse
+place('sfx', whoosh(0.6, 5000, 150, 0.7), T['cctvOut'] - 0.1, 0.4)
+place('hits', thump(80, 30, 1.6, 2.8), T['cctvOut'] + 0.4, 0.7, verb=0.35)
+
+# =================================================================== ACT 4 saturation
+sat0, cut = T['saturate'], T['cut']
+# pulse intensifies: 16ths, then doubled at the octave
+ostinato(52.5, cut, lambda t: 2400 + 3000 * (t - 52.5) / 8, lambda t: 0.12 + 0.06 * (t - 52.5) / 8)
+ostinato(55.5, cut, lambda t: 3000, lambda t: 0.05 + 0.06 * (t - 55.5) / 5, transpose=12)
+for i, t0 in enumerate(np.arange(52.5, cut, beat)):
+    k = (t0 - 52.5) / 8
+    place('perc', thump(100, 42, 0.55, 8, 40), t0, 0.5 + 0.25 * k, verb=0.15)
+    if t0 > 55.0:
+        place('perc', thump(100, 42, 0.4, 10, 40), t0 + beat / 2, 0.3 + 0.2 * k)
+    if i % 2 == 1:
+        sn = filt(noise(0.25), sos_bp(900, 5000)) * env_exp(0.25, 16) + sine(190, 0.25) * env_exp(0.25, 26) * 0.5
+        place('perc', sn, t0, 0.18 + 0.12 * k, verb=0.3)
+    # 32nd-note snare roll in the last bar
+    if t0 > 58.4:
+        for q in range(4):
+            sn = filt(noise(0.08), sos_bp(1200, 6000)) * env_exp(0.08, 40)
+            place('perc', sn, t0 + q * beat / 4, 0.1 + 0.05 * q)
+for k, t0 in enumerate(np.arange(52.5, cut, 2.0)):
+    nm, ch = prog[k % 4]
+    place('music', pad([note(x) for x in ch] + [note(x[:-1] + str(int(x[-1]) + 1)) for x in ch], 2.2, 1600 + k * 300, 0.3, 0.6), t0, 0.14, verb=0.3)
+# Shepard riser across the whole act
+sd = cut - sat0
+place('music', shepard(sd, 0.45, 40, 9, 0.12) * env_ar(sd, 2.5, 0.01, 1.3), sat0, 0.22, verb=0.2)
+place('sfx', riser(sd, 150, 9000), sat0, 0.25)
+# status lines type in
+for st in C['status']:
+    for j in range(14):
+        place('ui', click(4000 + rng.random() * 2000, 0.008), st + j * 0.028, 0.12, 0.4)
+    place('ui', blip(2093, 0.05, 0.2, 50), st + 0.42, 0.1, 0.4)
+# lattice building shimmer
+for j in range(400):
+    tc = T['twin'] + rng.random() ** 0.7 * (T['dishBreak'] - T['twin'])
+    place('ui', blip(4000 + rng.random() * 5000, 0.015, 0, 150), tc, 0.025, rng.uniform(-1, 1), verb=0.3)
+# containment alarm
+for j, tc in enumerate(np.arange(56.6, T['dishBreak'], 0.36)):
+    k = (tc - 56.6) / (T['dishBreak'] - 56.6)
+    tone = filt((np.sign(np.sin(2 * np.pi * 880 * tt(0.16))) * 0.4 + sine(880, 0.16)), sos_lp(2500)) * env_ar(0.16, 0.01, 0.05)
+    place('ui', tone, tc, 0.04 + 0.08 * k, 0.0, verb=0.2)
+    place('ui', filt((np.sign(np.sin(2 * np.pi * 660 * tt(0.16))) * 0.4 + sine(660, 0.16)), sos_lp(2500)) * env_ar(0.16, 0.01, 0.05), tc + 0.18, 0.04 + 0.08 * k, verb=0.2)
+# the breach: impact + shattering ring
+db = T['dishBreak']
+place('hits', braam(3.0, ('D1', 'A1', 'D2', 'A2'), 3200, 1.0, 1.2), db, 1.0, verb=0.4)
+place('hits', thump(120, 28, 2.5, 1.8, 14), db, 0.9)
+for j in range(220):
+    tc = db + (rng.random() ** 2.2) * 1.1
+    f = 2500 + rng.random() * 7000
+    gr = filt(noise(0.25), sos_bp(f * 0.97, f * 1.03)) * env_exp(0.25, 10 + rng.random() * 25)
+    place('sfx', gr, tc, 0.18 * (1 - (tc - db) / 1.2), rng.uniform(-1, 1), verb=0.3)
+# OMNIPRESENT
+om = T['omni']
+place('hits', braam(2.5, ('D1', 'D2', 'A2', 'D3'), 3800, 1.0, 0.8), om, 0.9, verb=0.45)
+place('ui', fm_bell(note('A6'), 1.5, 2.0, 1.2, 2.0), om, 0.08, verb=0.5)
+
+# =================================================================== ACT 5 title
+ti = T['title']
+# the hush after the cut, then a warm low bloom
+d = DUR - ti
+warm = (sine(note('D1'), d) * 0.6 + sine(note('A1') * 1.002, d) * 0.3 + sine(note('D2') * 0.998, d) * 0.2)
+warm *= np.interp(tt(d), [0, 0.8, 2.0, d - 3.5, d], [0, 0.4, 0.7, 0.6, 0])
+place('drone', warm, ti, 0.35)
+air = stereo_noise_bed(d, 2000, 12000) * np.interp(tt(d), [0, 1.5, d - 3, d], [0, 1, 1, 0])
+place('drone', air, ti, 0.012)
+# eye opens
+eo = T['eyeOpen']
+place('sfx', riser(0.9, 400, 7000), eo - 0.9, 0.18)
+place('hits', thump(70, 34, 2.5, 2.2), eo, 0.55, verb=0.4)
+for f, g in ((note('D6'), 0.06), (note('A6'), 0.05), (note('E7'), 0.035), (note('D5'), 0.05)):
+    place('music', fm_bell(f, 4.5, 2.0, 0.8, 0.8), eo, g, rng.uniform(-0.5, 0.5), verb=0.8)
+# wordmark: decode chatter then the warm hit
+wm = T['wordmark']
+for j in range(40):
+    place('ui', click(3000 + rng.random() * 4000, 0.007), wm + j * 0.022, 0.08, rng.uniform(-0.4, 0.4))
+place('hits', braam(6.0, ('D1', 'A1', 'D2', 'E2'), 1400, 1.0, 0.5), wm + 0.85, 0.7, verb=0.5)
+place('music', pad([note(x) for x in ('D3', 'A3', 'E4', 'F#4', 'A4')], 7.5, 1400, 1.5, 3.5), wm + 0.85, 0.16, verb=0.5)
+# tagline keystrokes
+tg_t = T['tagline']
+for j, ch in enumerate('NO PLACE LEFT BEHIND.'):
+    if ch != ' ':
+        place('ui', click(3800 + rng.random() * 1500, 0.009), tg_t + j / 22, 0.14)
+# ONLINE
+on = T['online']
+place('ui', blip(note('A5'), 0.12, 0.3, 18), on, 0.16, verb=0.5)
+place('ui', blip(note('D6'), 0.35, 0.3, 8), on + 0.12, 0.16, verb=0.6)
+place('hits', thump(60, 30, 3.5, 1.4, 10), on, 0.6, verb=0.5)
+place('music', pad([note(x) for x in ('D2', 'A2', 'D3', 'E3', 'A3')], DUR - on, 900, 0.8, 3.5), on, 0.12, verb=0.4)
+
+# =================================================================== reverb
+def make_ir(rt60=3.4, pre=0.025):
+    n = int((rt60 + pre) * SR)
+    t0 = np.arange(n) / SR
+    ir = np.zeros((2, n))
+    for c in range(2):
+        x = rng.standard_normal(n) * np.exp(-6.9 * t0 / rt60)
+        # darker tail: blend toward a lowpassed copy over time
+        lp = filt(x, sos_lp(2500))
+        mix = np.clip(t0 / 1.5, 0, 1)
+        ir[c] = x * (1 - mix) + lp * mix
+        ir[c, : int(pre * SR)] = 0
+    return ir / np.sqrt(np.sum(ir ** 2) / 2)
+
+
+ir = make_ir()
+wet = np.vstack([signal.fftconvolve(B['verb'][c], ir[c])[:N] for c in range(2)])
+
+# =================================================================== mix + master
+# pre-hit dips: the bed drops out for a beat so each impact lands in a hole
+dip = np.ones(N)
+for ht, depth in ((T['substrate'], 0.3), (T['indexed'], 0.25), (T['cctvWall'], 0.4), (T['cctvOut'] + 0.4, 0.4), (T['dishBreak'], 0.2), (T['omni'], 0.45), (T['wordmark'] + 0.85, 0.4)):
+    a, b, c = int((ht - 0.28) * SR), int((ht - 0.03) * SR), int((ht + 0.5) * SR)
+    dip[a:b] = np.minimum(dip[a:b], np.linspace(1, depth, b - a))
+    dip[b:c] = np.minimum(dip[b:c], np.linspace(depth, 1, c - b) ** 0.7)
+bed_mix = (B['drone'] * 1.0 + B['music'] * 0.9 + B['perc'] * 0.8 + B['sfx'] * 0.9 + B['ui'] * 0.85) * dip
+mix = bed_mix + B['hits'] * 1.25 + wet * 0.32
+mix = filt(mix, sos_hp(24, 2))
+
+# glitch stutter into the cut, then hard silence until the title
+def stutter(x, a, b, slice_s=0.045):
+    ia, ib = int(a * SR), int(b * SR)
+    sl = int(slice_s * SR)
+    src = x[:, ia:ia + sl].copy()
+    for i in range(ia, ib, sl):
+        n = min(sl, ib - i)
+        x[:, i:i + n] = src[:, :n] * (0.9 if ((i - ia) // sl) % 2 == 0 else 0.6)
+    return x
+
+
+mix = stutter(mix, cut - 0.22, cut, 0.04)
+ic = int(cut * SR)
+it = int(T['title'] * SR)
+fade = int(0.004 * SR)
+mix[:, ic - fade:ic] *= np.linspace(1, 0, fade)
+mix[:, ic:it] = 0
+# collapse glitch: tiny stutter as the console implodes
+mix = stutter(mix, T['collapse'] + 0.02, T['collapse'] + 0.14, 0.03)
+
+# glue: slow RMS compressor, then soft clip and a lookahead peak limiter
+def rms_env(x, win_s=0.05):
+    w = int(win_s * SR)
+    p = np.mean(x ** 2, axis=0)
+    k = np.ones(w) / w
+    return np.sqrt(np.convolve(p, k, mode='same') + 1e-12)
+
+
+env = rms_env(mix, 0.08)
+thr = 10 ** (-15 / 20)
+ratio = 1.8
+gain = np.where(env > thr, (thr * (env / thr) ** (1 / ratio)) / env, 1.0)
+gain = signal.sosfiltfilt(sos_lp(8), gain)
+mix *= gain
+mix = np.tanh(mix * 1.6) / 1.6
+
+look = int(0.004 * SR)
+peak = np.max(np.abs(mix), axis=0)
+peak = np.lib.stride_tricks.sliding_window_view(np.pad(peak, (0, look)), look + 1).max(axis=1)[:N]
+ceiling = 10 ** (-1.2 / 20)
+lg = np.minimum(1.0, ceiling / np.maximum(peak, 1e-9))
+lg = np.minimum.reduce([lg, np.roll(lg, 1), np.roll(lg, -1)])
+lg = signal.sosfiltfilt(sos_lp(60), lg)
+mix *= np.minimum(lg, 1.0)
+mix *= ceiling / max(1e-9, np.max(np.abs(mix)))
+
+out = os.path.join(HERE, 'score.wav')
+wavfile.write(out, SR, (mix.T * (2 ** 31 - 1)).astype(np.int32))
+print('wrote', out, f'{DUR}s', 'peak', np.max(np.abs(mix)))

intro-sequence/audio/sfx.py

@@ -0,0 +1,527 @@
+#!/usr/bin/env python3
+"""God's Eye View — First Light (v2): sound design, built to sit under a music track.
+
+No melody, no beeps. Sub, air, metal, impacts, swells, data texture — a tech
+thriller palette that leaves the mids for the score. Everything is synthesised
+and placed against audio/cues.json (exported from src/timeline.js).
+
+    python3 audio/sfx.py   -> audio/sfx.wav (48 kHz, 24-bit stereo)
+"""
+import json
+import os
+import numpy as np
+from scipy import signal
+from scipy.io import wavfile
+
+SR = 48000
+HERE = os.path.dirname(os.path.abspath(__file__))
+C = json.load(open(os.path.join(HERE, 'cues.json')))
+T = C['T']
+DUR = C['DURATION']
+N = int(SR * DUR)
+rng = np.random.default_rng(20261019)
+
+B = {k: np.zeros((2, N)) for k in ('bed', 'hits', 'fx', 'ui', 'verb')}
+
+
+def place(dst, sig, t, gain=1.0, pan=0.0, verb=0.0):
+    if sig.ndim == 1:
+        p = (pan + 1) * np.pi / 4
+        sig = np.vstack([sig * np.cos(p), sig * np.sin(p)])
+    i0 = int(round(t * SR))
+    if i0 >= N:
+        return
+    s0 = max(0, -i0)
+    i0 = max(0, i0)
+    n = min(sig.shape[1] - s0, N - i0)
+    if n <= 0:
+        return
+    seg = sig[:, s0:s0 + n] * gain
+    B[dst][:, i0:i0 + n] += seg
+    if verb > 0:
+        B['verb'][:, i0:i0 + n] += seg * verb
+
+
+def tt(d):
+    return np.arange(int(d * SR)) / SR
+
+
+def lp(fc, o=2):
+    return signal.butter(o, min(fc, SR * 0.45), 'low', fs=SR, output='sos')
+
+
+def hp(fc, o=2):
+    return signal.butter(o, max(fc, 10), 'high', fs=SR, output='sos')
+
+
+def bp(lo, hi, o=2):
+    lo = max(lo, 10)
+    hi = min(max(hi, lo * 1.05), SR * 0.45)
+    return signal.butter(o, [lo, hi], 'band', fs=SR, output='sos')
+
+
+def F(x, sos):
+    return signal.sosfilt(sos, x, axis=-1)
+
+
+def sweep(x, fn, kind='low', block=256):
+    y = np.zeros_like(x)
+    zi = None
+    for b in range(0, len(x), block):
+        fc = float(fn(b / SR))
+        sos = lp(fc) if kind == 'low' else hp(fc) if kind == 'high' else bp(fc * 0.7, fc * 1.35)
+        if zi is None:
+            zi = signal.sosfilt_zi(sos) * 0
+        y[b:b + block], zi = signal.sosfilt(sos, x[b:b + block], zi=zi)
+    return y
+
+
+def noise(d):
+    return rng.standard_normal(int(d * SR))
+
+
+def env_exp(d, k, a=0.002):
+    t = tt(d)
+    return np.minimum(1, t / max(a, 1e-4)) * np.exp(-t * k)
+
+
+def env_ar(d, a, r, c=2.0):
+    t = tt(d)
+    return np.minimum(np.clip(t / max(a, 1e-4), 0, 1) ** c, np.clip((d - t) / max(r, 1e-4), 0, 1) ** c)
+
+
+def sine(f, d, ph=0.0):
+    t = tt(d)
+    if np.isscalar(f):
+        return np.sin(2 * np.pi * f * t + ph)
+    return np.sin(2 * np.pi * np.cumsum(f) / SR + ph)
+
+
+def saw(f, d):
+    t = tt(d)
+    ph = f * t if np.isscalar(f) else np.cumsum(f) / SR
+    return 2 * (ph - np.floor(ph + 0.5))
+
+
+# ---------------------------------------------------------------- designed sounds
+def tick(d=0.006, f=5000, q=0.6):
+    """A dry, expensive-sounding UI tick: filtered noise, no pitch."""
+    return F(noise(d) * env_exp(d, 1200, 0.0002), bp(f * (1 - q / 2), f * (1 + q)))
+
+
+def granule(f=6000):
+    d = 0.012 + rng.random() * 0.02
+    return F(noise(d) * env_ar(d, 0.002, d * 0.8), bp(f * 0.8, f * 1.25))
+
+
+def sub_boom(d=3.0, f0=55, f1=24, k=1.4):
+    t = tt(d)
+    f = f1 + (f0 - f1) * np.exp(-t * 7)
+    return sine(f, d) * env_exp(d, k, 0.003)
+
+
+def metal(d=3.0, base=180.0, k=1.2):
+    """Inharmonic struck-metal resonance — the cinematic 'tail'."""
+    t = tt(d)
+    out = np.zeros(len(t))
+    for r, a in ((1.0, 1.0), (2.76, 0.6), (5.4, 0.45), (8.93, 0.3), (13.3, 0.2), (1.51, 0.5)):
+        out += a * np.sin(2 * np.pi * base * r * (1 + 0.002 * rng.standard_normal()) * t + rng.random() * 6) * np.exp(-t * k * (0.6 + r * 0.25))
+    return out / 3.0
+
+
+def crack(d=0.4):
+    return F(noise(d) * env_exp(d, 18, 0.0005), bp(400, 7000))
+
+
+def impact(size=1.0, dark=0.0, tail=3.5, base=150):
+    """Trailer hit: sub drop + body thud + noise crack + metallic tail."""
+    d = tail + 0.5
+    s = sub_boom(d, 62, 22, 1.1) * 1.0
+    body = F(noise(0.5) * env_exp(0.5, 9, 0.001), lp(420)) * 0.9
+    out = s
+    out[: len(body)] += body
+    c = crack(0.45) * (0.5 - dark * 0.35)
+    out[: len(c)] += c
+    m = metal(d, base * (1 - dark * 0.3), 1.0) * 0.28
+    out += F(m, lp(4000 - dark * 2500))
+    return np.tanh(out * 1.4 * size) * 0.8
+
+
+def braam(d=4.0, root=36.71, bright=1400, gain=1.0):
+    """Low, distorted brass-like swell — filtered and dirty, not synthy."""
+    acc = np.zeros(int(d * SR))
+    for mult in (1, 1.5, 2, 3):
+        for det in (-0.01, 0, 0.012):
+            acc += saw(root * mult * (1 + det), d)
+    acc /= 10
+    y = sweep(acc, lambda tc: 120 + bright * min(1, tc / 0.09) * np.exp(-max(0, tc - 0.09) * 1.3))
+    y = np.tanh(y * 3.0) * env_ar(d, 0.015, d * 0.85, 1.2)
+    return y * gain
+
+
+def whoosh(d=1.0, f0=300, f1=4000, peak=0.55, width=0.06):
+    x = noise(d)
+    y = sweep(x, lambda tc: f0 * (f1 / f0) ** min(1, tc / d), 'band')
+    t0 = tt(d)
+    return y * np.exp(-((t0 / d - peak) ** 2) / width)
+
+
+def swell(d=1.5, f0=200, f1=6000):
+    """Reverse-swell into a hit."""
+    x = noise(d)
+    y = sweep(x, lambda tc: f0 * (f1 / f0) ** ((tc / d) ** 1.8), 'band')
+    t0 = tt(d)
+    m = metal(d, 220, 0.2)[::-1] * 0.25
+    return (y + m) * (t0 / d) ** 2.6
+
+
+def servo(d=0.6, f0=180, f1=420):
+    t0 = tt(d)
+    f = f0 + (f1 - f0) * np.sin(np.pi * t0 / d / 2)
+    x = saw(f, d) + 0.4 * saw(f * 2.01, d)
+    return F(x, bp(200, 2200)) * env_ar(d, 0.05, 0.12) * 0.5
+
+
+def glitch(d=0.25):
+    """Digital stutter: gated, bit-crushed noise and a buzzing carrier."""
+    x = noise(d)
+    gate = (np.sin(2 * np.pi * (35 + rng.random() * 40) * tt(d)) > 0).astype(float)
+    crushed = np.round(x * 4) / 4
+    buzz = np.sign(np.sin(2 * np.pi * (90 + rng.random() * 80) * tt(d))) * 0.3
+    return F((crushed * 0.6 + buzz) * gate, bp(300, 9000)) * env_ar(d, 0.002, 0.03)
+
+
+def drone_bed(d, notes=(36.71, 55.0, 73.42), lpf=180):
+    t0 = tt(d)
+    x = sum(np.sin(2 * np.pi * f * (1 + 0.0008 * k) * t0 + k) * (0.6 / (k + 1)) for k, f in enumerate(notes))
+    x += F(noise(d), lp(lpf)) * 0.25
+    return x
+
+
+def tension(d, base=55.0):
+    """Dissonant cluster, heavily low-passed: dread, not tune."""
+    t0 = tt(d)
+    x = np.zeros(len(t0))
+    for r in (1.0, 1.059, 1.5, 2.12, 2.0):
+        x += saw(base * r * (1 + 0.003 * np.sin(2 * np.pi * 0.07 * t0 * r)), d)
+    x = F(x / 5, lp(380))
+    return x * (0.7 + 0.3 * np.sin(2 * np.pi * 0.11 * t0))
+
+
+def rotor(d, rate=5.6):
+    t0 = tt(d)
+    thump = (0.5 + 0.5 * np.sin(2 * np.pi * rate * t0)) ** 6
+    x = F(noise(d), lp(220)) * thump * 1.6 + F(noise(d), bp(900, 3000)) * thump * 0.08
+    return x
+
+
+def jet(d):
+    t0 = tt(d)
+    whine = sine(2400 + 120 * np.sin(2 * np.pi * 0.2 * t0), d) * 0.04 + sine(3600, d) * 0.015
+    roar = F(noise(d), bp(120, 900)) * 0.6
+    return roar + whine
+
+
+def wind(d):
+    a = sweep(noise(d), lambda tc: 260 + 500 * (0.5 + 0.5 * np.sin(tc * 0.9)), 'band')
+    b = sweep(noise(d), lambda tc: 300 + 600 * (0.5 + 0.5 * np.sin(tc * 0.7 + 1.3)), 'band')
+    return np.vstack([a, b])
+
+
+def squelch(d=0.35):
+    x = F(noise(d), bp(800, 4500)) * env_ar(d, 0.005, 0.06)
+    return x
+
+
+def heartbeat(t, g=1.0):
+    for dt, gg, f0 in ((0.0, 1.0, 64), (0.19, 0.55, 54)):
+        d = 0.7
+        t0 = tt(d)
+        f = 30 + (f0 - 30) * np.exp(-t0 * 28)
+        place('hits', sine(f, d) * env_exp(d, 7.5, 0.002), t + dt, g * gg, verb=0.2)
+
+
+# =================================================================== the film
+t_all = tt(DUR)
+# bed: sub + air, riding an intensity curve, silent through the cut
+inten = np.interp(t_all, [0, 4, 9, 16, 30, 43, 44, 72, 76.6, T['cut'] - 0.01, T['cut'], T['title'], T['title'] + 3, DUR - 2.5, DUR],
+                  [0, 0.25, 0.4, 0.55, 0.65, 0.7, 0.55, 0.65, 0.75, 1.0, 0, 0, 0.6, 0.5, 0])
+bed = drone_bed(DUR) * inten
+B['bed'] += np.vstack([bed, bed]) * 0.32
+airbed = np.vstack([F(noise(DUR), bp(2500, 11000)), F(noise(DUR), bp(2500, 11000))]) * 0.012 * inten
+B['bed'] += airbed
+# tension cluster under the indexing and the cities
+tz = tension(DUR) * np.interp(t_all, [16, 20, 30, 31, 43, 44, 70, 76, 84.4, 84.41], [0, 0.5, 0.6, 0.35, 0.45, 0.6, 0.7, 0.8, 1.0, 0], left=0, right=0)
+B['bed'] += np.vstack([tz, tz * 0.95]) * 0.22
+
+# ACT 0 — console
+hum = (sine(100, DUR) * 0.25 + F(noise(DUR), bp(80, 300)) * 0.05) * np.interp(t_all, [0.4, 1.2, T['collapse'], T['seed']], [0, 1, 1, 0], left=0, right=0)
+place('fx', hum, 0, 0.12)
+for k in C['boot']:
+    if k['ch'] != ' ':
+        place('ui', tick(0.006, 4200 + rng.random() * 2500), k['t'], 0.16, pan=(rng.random() - 0.5) * 0.3)
+place('fx', swell(T['seed'] - T['collapse'] + 0.05, 300, 9000), T['collapse'], 0.35)
+place('fx', glitch(0.18), T['collapse'], 0.25)
+place('hits', impact(0.7, dark=0.6, tail=3.0, base=110), T['seed'], 0.8, verb=0.35)
+for bt in (T['beat1'], T['beat2']):
+    heartbeat(bt, 1.1)
+# aperture: servos as the blades retract
+place('fx', servo(1.2, 140, 360), T['aperture'], 0.22, -0.3, verb=0.2)
+place('fx', servo(1.0, 160, 300), T['aperture'] + 0.25, 0.18, 0.3, verb=0.2)
+for i in range(120):
+    place('ui', tick(0.004, 7000 if i % 10 else 4200), T['dishDraw'] + (i / 120) * (T['dishDone'] - T['dishDraw']), 0.05 if i % 10 else 0.1, pan=np.sin(i / 120 * 6.28) * 0.8)
+
+# ACT 1 — growth: organic granular crackle densifying
+gs, ge = T['growStart'], T['growEnd']
+for _ in range(2400):
+    x = rng.random() ** 0.45
+    tc = gs + x * (ge - gs + 0.3)
+    k = (np.exp(3 * (tc - gs) / (ge - gs)) - 1) / (np.exp(3) - 1)
+    if rng.random() > 0.15 + 0.85 * k:
+        continue
+    place('fx', granule(2000 + rng.random() * 7000), tc, 0.05 + 0.08 * rng.random() * (0.4 + k), pan=rng.uniform(-0.9, 0.9))
+# radar sweep: a slow low whoosh per revolution
+sweep_period = 2 * np.pi / 2.4
+for i in range(int((T['substrate'] - gs) / sweep_period) + 1):
+    place('fx', whoosh(sweep_period, 120, 900, 0.5, 0.12), gs + i * sweep_period, 0.08, pan=0.0)
+place('fx', swell(1.6, 120, 5000), T['substrate'] - 1.6, 0.3)
+place('hits', impact(0.9, 0.2, 4.0, 150), T['substrate'], 0.9, verb=0.35)
+place('hits', braam(3.5, 36.71, 1100), T['substrate'], 0.35, verb=0.3)
+
+# ACT 2 — indexing: tiles as data grains, captures as shutter clicks
+for tl in C['tiles']:
+    if not tl['vis'] or tl['t'] > 23.5:
+        continue
+    if tl['z'] == 5 and rng.random() > 0.3:
+        continue
+    place('ui', granule(3000 + rng.random() * 5000), tl['t'], {3: 0.07, 4: 0.04, 5: 0.025}[tl['z']], pan=tl['pan'] * 0.8)
+
+
+def shutter(t, g=1.0, pan=0.0):
+    place('fx', tick(0.008, 3800, 0.6), t, 0.45 * g, pan)
+    place('fx', tick(0.014, 2100, 0.6), t + 0.045, 0.35 * g, pan)
+    place('fx', F(noise(0.05) * env_exp(0.05, 60), lp(500)), t, 0.25 * g, pan)
+
+
+for cp in C['caps']:
+    if cp['slow']:
+        shutter(cp['t'], 1.0, -0.3)
+        place('fx', servo(0.9, 220, 900), cp['t'] + 0.3, 0.12, -0.3, verb=0.2)
+        place('fx', whoosh(0.45, 900, 5000, 0.5), cp['t'] + 1.15, 0.16, 0.4)
+    else:
+        shutter(cp['t'], 0.5, 0.5)
+# the flurry: shutters dissolving into a roar of capture
+fl0, fl1 = T['flurry'], T['flurryEnd']
+for i in range(420):
+    u = rng.random() ** 0.6
+    tc = fl0 + u * (fl1 - fl0)
+    shutter(tc, 0.18 + 0.25 * u, rng.uniform(-0.9, 0.9))
+sw_d = fl1 - fl0
+spin = whoosh(sw_d, 150, 3500, 0.62, 0.05)
+place('fx', np.vstack([spin, np.roll(spin, 900)]), fl0, 0.35)
+place('fx', swell(1.2, 200, 8000), T['indexed'] - 1.2, 0.35)
+place('hits', impact(1.1, 0.0, 4.5, 170), T['indexed'], 1.0, verb=0.4)
+place('hits', braam(4.0, 36.71, 1800), T['indexed'], 0.4, verb=0.3)
+
+# ACT 3 — feeds: each a designed arrival, not a beep
+def feed(key, t):
+    place('ui', tick(0.01, 3000), t, 0.25, -0.5)
+    place('fx', whoosh(0.5, 2500, 400, 0.3), t - 0.05, 0.12, -0.4)
+    if key == 'air':
+        for _ in range(380):
+            place('ui', tick(0.003, 6000 + rng.random() * 3000), t + rng.random() ** 0.7 * 1.6, 0.04 + rng.random() * 0.04, rng.uniform(-0.9, 0.9))
+        place('fx', jet(1.6) * env_ar(1.6, 0.3, 1.0), t, 0.25, 0.3)
+    elif key == 'sea':
+        p = sine(820 * np.exp(-tt(2.5) * 0.06), 2.5) * env_exp(2.5, 2.0)
+        place('fx', F(p, lp(2000)), t + 0.05, 0.12, 0.2, verb=0.9)
+        place('fx', F(noise(2.0), lp(300)) * env_ar(2.0, 0.6, 1.2), t, 0.25)
+    elif key == 'mil':
+        place('fx', squelch(0.3), t + 0.05, 0.25, 0.4)
+        place('fx', F(saw(48, 1.2), bp(60, 600)) * env_ar(1.2, 0.1, 0.8), t, 0.18)
+    elif key == 'orbit':
+        place('fx', whoosh(2.6, 2600, 160, 0.4, 0.1), t + 0.2, 0.3)
+        place('hits', sub_boom(2.0, 48, 24, 2.0), t + 0.1, 0.5, verb=0.3)
+        for _ in range(40):
+            place('ui', granule(7000 + rng.random() * 4000), t + rng.random() * 2.0, 0.03, rng.uniform(-1, 1), verb=0.6)
+    elif key == 'quake':
+        for j, dt in enumerate((0.05, 0.45, 0.95)):
+            place('hits', sub_boom(1.4, 50, 22, 3.0), t + dt, 0.6 - j * 0.12, verb=0.25)
+        place('fx', F(noise(2.4), lp(90)) * env_ar(2.4, 0.2, 1.6), t, 1.0)
+    elif key == 'fire':
+        for _ in range(700):
+            x = rng.random() ** 1.3 * 2.0
+            place('fx', granule(700 + rng.random() * 4000), t + x, (1 - x / 2) * 0.1 * rng.random(), rng.uniform(-0.8, 0.8))
+        place('fx', F(noise(2.0), bp(150, 1200)) * env_ar(2.0, 0.05, 1.5), t, 0.08)
+    elif key == 'wind':
+        place('fx', wind(2.6) * env_ar(2.6, 0.5, 1.5), t, 0.45)
+    elif key == 'cable':
+        buzz = F(saw(60, 1.5) + 0.5 * saw(120.4, 1.5), bp(300, 2500)) * env_ar(1.5, 0.02, 0.9)
+        place('fx', buzz, t, 0.05, 0.2)
+        place('fx', glitch(0.2), t, 0.12, -0.2)
+
+
+for fd in C['feeds']:
+    feed(fd['key'], fd['t'])
+for t0, d in ((31.6, 1.8), (33.6, 2.2), (35.0, 2.2)):
+    place('fx', whoosh(d, 200, 2400, 0.5), t0, 0.16, rng.uniform(-0.5, 0.5))
+
+# ACT 4 — descent and the cities
+place('fx', swell(1.4, 120, 9000), T['terrain'] - 1.4, 0.45)
+place('fx', whoosh(1.2, 4000, 120, 0.7, 0.08), T['terrain'] - 1.0, 0.4)
+place('hits', impact(1.0, 0.4, 3.5, 120), T['terrain'], 0.85, verb=0.4)
+for c in C['cities']:
+    t0, t1 = c['t0'], c['t1']
+    d = t1 - t0
+    if c['slug'] != 'everest':
+        place('fx', glitch(0.22), t0 - 0.05, 0.35)
+        place('hits', impact(0.6, 0.5, 2.5, 140), t0, 0.5, verb=0.3)
+        place('fx', whoosh(0.6, 3000, 300, 0.25), t0 - 0.1, 0.25)
+    amb = F(noise(d), bp(60, 400)) * env_ar(d, 0.4, 0.4) * 0.5
+    place('fx', np.vstack([amb, np.roll(amb, 2000)]), t0, 0.25)
+    if c['slug'] == 'everest':
+        place('fx', wind(d) * env_ar(d, 0.6, 0.6), t0, 0.7)
+        # LiDAR sweep: a soft rising tone per pass
+        for i in range(int(d / (1 / 0.35 * 1.2 / 1.2)) + 1):
+            place('fx', F(sine(np.linspace(300, 1200, int(1.2 * SR)), 1.2), bp(200, 1600)) * env_ar(1.2, 0.3, 0.6), t0 + i * 2.86, 0.03, verb=0.4)
+    elif c['slug'] == 'nyc':
+        traffic = F(noise(d), bp(80, 700)) * env_ar(d, 0.8, 0.5)
+        place('fx', np.vstack([traffic, np.roll(traffic, 5000)]), t0, 0.22)
+        place('fx', rotor(d) * env_ar(d, 1.0, 1.0), t0 + 0.2, 0.3, 0.4)
+        for j in range(8):
+            place('fx', tick(0.01, 2400), t0 + 2.2 + j * 0.35, 0.18, 0.7)
+            place('fx', F(noise(0.1), bp(1500, 7000)) * env_exp(0.1, 25), t0 + 2.2 + j * 0.35, 0.05, 0.7)
+    elif c['slug'] == 'boston':
+        for j in range(4):
+            place('fx', F(noise(1.4), bp(100, 900)) * env_ar(1.4, 0.4, 0.8) * (1 + 0.3 * np.sin(2 * np.pi * 9 * tt(1.4))), t0 + 0.6 + j * 1.0, 0.1, rng.uniform(-0.7, 0.7))
+    elif c['slug'] == 'lax':
+        place('fx', jet(d) * env_ar(d, 0.8, 0.8), t0, 0.35, -0.3)
+        place('fx', whoosh(2.4, 200, 1400, 0.5, 0.1), t0 + 1.4, 0.3, 0.5)
+    elif c['slug'] == 'bragg':
+        place('fx', rotor(d, 4.6) * env_ar(d, 0.8, 0.8), t0 + 0.4, 0.25, -0.4)
+        for j in range(3):
+            place('fx', squelch(0.3), t0 + 0.8 + j * 1.3, 0.16, 0.5)
+
+# the camera wall
+wt = T['cctvWall']
+place('hits', impact(0.9, 0.3, 3.0, 160), wt, 0.8, verb=0.3)
+place('hits', braam(3.0, 36.71, 1400), wt, 0.3, verb=0.3)
+for _ in range(100):
+    tc = wt + rng.random() ** 0.8 * 0.85 + rng.random() * 0.12
+    place('fx', tick(0.012, 2200 + rng.random() * 2000), tc, 0.14, rng.uniform(-0.95, 0.95))
+    place('fx', F(noise(0.08), bp(1500, 8000)) * env_exp(0.08, 30), tc, 0.03, rng.uniform(-0.95, 0.95))
+wd = T['cctvOut'] - wt + 0.3
+place('fx', np.vstack([F(noise(wd), bp(800, 6000)), F(noise(wd), bp(800, 6000))]) * env_ar(wd, 0.4, 0.25), wt, 0.035)
+for j in range(int((T['cctvOut'] - wt - 0.8) * 7)):
+    place('ui', tick(0.006, 5200), wt + 0.8 + j / 7, 0.06, rng.uniform(-0.8, 0.8))
+place('fx', whoosh(0.6, 5000, 150, 0.7), T['cctvOut'] - 0.1, 0.4)
+place('hits', impact(0.9, 0.5, 3.0, 120), T['cctvOut'] + 0.4, 0.7, verb=0.35)
+
+# ACT 5 — saturation: rising pressure, the breach, the state
+sat0, cut = T['saturate'], T['cut']
+sd = cut - sat0
+t0s = tt(sd)
+pos = 0.45 * t0s + 0.06 * t0s ** 2
+sh = np.zeros(len(t0s))
+for k in range(9):
+    o = (k + pos) % 9
+    a = np.exp(-((o - 4.5) ** 2) / (2 * 1.8 ** 2))
+    sh += np.sin(2 * np.pi * np.cumsum(30 * 2 ** o) / SR) * a
+sh = F(sh / 9 * 2, lp(2200)) * env_ar(sd, 2.0, 0.01, 1.3)
+place('fx', sh, sat0, 0.3, verb=0.2)
+place('fx', swell(sd, 120, 9000), sat0, 0.3)
+# pulse of low hits accelerating toward the breach
+tk = sat0 + 0.5
+gap = 0.9
+while tk < T['dishBreak'] - 0.2:
+    place('hits', sub_boom(0.9, 58, 30, 4.0), tk, 0.35 + 0.35 * (tk - sat0) / sd)
+    place('fx', F(noise(0.12), bp(500, 4000)) * env_exp(0.12, 30), tk, 0.08)
+    tk += gap
+    gap = max(0.22, gap * 0.86)
+for st in C['status']:
+    for j in range(16):
+        place('ui', tick(0.005, 4500 + rng.random() * 1500), st + j * 0.026, 0.1, 0.4)
+for _ in range(300):
+    tc = T['twin'] + rng.random() ** 0.7 * (T['dishBreak'] - T['twin'])
+    place('ui', granule(5000 + rng.random() * 5000), tc, 0.025, rng.uniform(-1, 1), verb=0.3)
+db = T['dishBreak']
+place('hits', impact(1.25, 0.0, 5.0, 190), db, 1.1, verb=0.45)
+place('hits', braam(3.0, 36.71, 2600), db, 0.45, verb=0.4)
+for _ in range(200):
+    tc = db + rng.random() ** 2.2 * 1.1
+    f = 2500 + rng.random() * 7000
+    g = F(noise(0.25), bp(f * 0.97, f * 1.03)) * env_exp(0.25, 10 + rng.random() * 25)
+    place('fx', g, tc, 0.16 * (1 - (tc - db) / 1.2), rng.uniform(-1, 1), verb=0.3)
+place('hits', impact(1.0, 0.3, 4.0, 110), T['omni'], 0.8, verb=0.45)
+
+# ACT 6 — title: low bloom, the eye, the word
+ti = T['title']
+d = DUR - ti
+warm = drone_bed(d, (36.71, 55.0, 73.42, 110.0), 140) * np.interp(tt(d), [0, 0.8, 2.0, d - 3.0, d], [0, 0.4, 0.7, 0.6, 0])
+place('bed', warm, ti, 0.3)
+place('fx', swell(0.9, 400, 7000), T['eyeOpen'] - 0.9, 0.2)
+place('hits', impact(0.8, 0.6, 5.0, 90), T['eyeOpen'], 0.6, verb=0.5)
+place('fx', metal(6.0, 220, 0.5) * 0.4, T['eyeOpen'], 0.12, verb=0.7)
+for j in range(36):
+    place('ui', tick(0.006, 3500 + rng.random() * 4000), T['wordmark'] + j * 0.024, 0.07, rng.uniform(-0.4, 0.4))
+place('hits', impact(1.0, 0.4, 6.5, 100), T['wordmark'] + 0.85, 0.8, verb=0.55)
+place('hits', braam(6.0, 36.71, 900), T['wordmark'] + 0.85, 0.35, verb=0.5)
+for j in range(11):
+    place('ui', tick(0.008, 4000), T['tagline'] + j * 0.08, 0.1)
+place('fx', metal(6.0, 330, 0.45) * 0.35, T['tagline'] + 0.9, 0.1, verb=0.8)
+
+# =================================================================== reverb, mix, master
+def ir(rt=3.6, pre=0.03):
+    n = int((rt + pre) * SR)
+    t0 = np.arange(n) / SR
+    out = np.zeros((2, n))
+    for c in range(2):
+        x = rng.standard_normal(n) * np.exp(-6.9 * t0 / rt)
+        l2 = F(x, lp(2200))
+        m = np.clip(t0 / 1.2, 0, 1)
+        out[c] = x * (1 - m) + l2 * m
+        out[c, : int(pre * SR)] = 0
+    return out / np.sqrt(np.sum(out ** 2) / 2)
+
+
+R = ir()
+wet = np.vstack([signal.fftconvolve(B['verb'][c], R[c])[:N] for c in range(2)])
+dip = np.ones(N)
+for ht, depth in ((T['substrate'], 0.3), (T['indexed'], 0.25), (T['terrain'], 0.3), (T['cctvWall'], 0.4), (T['dishBreak'], 0.2), (T['wordmark'] + 0.85, 0.4)):
+    a, b, c = int((ht - 0.28) * SR), int((ht - 0.03) * SR), int((ht + 0.5) * SR)
+    dip[a:b] = np.minimum(dip[a:b], np.linspace(1, depth, b - a))
+    dip[b:c] = np.minimum(dip[b:c], np.linspace(depth, 1, c - b) ** 0.7)
+mix = (B['bed'] + B['fx'] * 0.9 + B['ui'] * 0.8) * dip + B['hits'] * 1.2 + wet * 0.3
+mix = F(mix, hp(22))
+
+
+def stutter(x, a, b, sl=0.04):
+    ia, ib, s = int(a * SR), int(b * SR), int(sl * SR)
+    src = x[:, ia:ia + s].copy()
+    for i in range(ia, ib, s):
+        n = min(s, ib - i)
+        x[:, i:i + n] = src[:, :n] * (0.9 if ((i - ia) // s) % 2 == 0 else 0.55)
+    return x
+
+
+mix = stutter(mix, cut - 0.22, cut)
+ic, it = int(cut * SR), int(T['title'] * SR)
+f = int(0.004 * SR)
+mix[:, ic - f:ic] *= np.linspace(1, 0, f)
+mix[:, ic:it] = 0
+
+# gentle glue + ceiling
+p = np.sqrt(np.convolve(np.mean(mix ** 2, axis=0), np.ones(4000) / 4000, mode='same') + 1e-12)
+thr = 10 ** (-16 / 20)
+g = np.where(p > thr, (thr * (p / thr) ** (1 / 1.8)) / p, 1.0)
+g = signal.sosfiltfilt(lp(8), g)
+mix *= g
+mix = np.tanh(mix * 1.5) / 1.5
+look = int(0.004 * SR)
+pk = np.lib.stride_tricks.sliding_window_view(np.pad(np.max(np.abs(mix), axis=0), (0, look)), look + 1).max(axis=1)[:N]
+ceil = 10 ** (-1.2 / 20)
+lg = signal.sosfiltfilt(lp(60), np.minimum(1.0, ceil / np.maximum(pk, 1e-9)))
+mix *= np.minimum(lg, 1.0)
+mix *= ceil / max(1e-9, np.max(np.abs(mix)))
+out = os.path.join(HERE, 'sfx.wav')
+wavfile.write(out, SR, (mix.T * (2 ** 31 - 1)).astype(np.int32))
+print('wrote', out, DUR, 's')

intro-sequence/data/SOURCES.md

@@ -0,0 +1,62 @@
+# Intro-sequence data snapshot: sources
+
+All files are real downloads from public keyless endpoints, fetched on **2026-10-18 between 02:24 and 02:42 UTC**. Nothing here is synthesized. The scripts only filter, convert units and round. Helper scripts are in `../tools/fetch/` (`fetch_basic.sh`, `process_basic.py`, `process_tle.py`, `process_vessels.py`, `fetch_wind.py`, `fetch_bonus.py`, `cctv_fetch.py`, `cctv_select.py`).
+
+JSON files are compact. Tabular layers use `{"cols":[...],"rows":[[...],...]}`, and each file's `cols` lists its columns. Coordinates are `[lon, lat]` in WGS84.
+
+| File | Rows | Source URL(s) | Fetched (UTC) | Notes / licence |
+|---|---|---|---|---|
+| `flights.json` | 5,550 airborne aircraft | https://opensky-network.org/api/states/all | 02:24:18 (`t`=1792290258) | OpenSky Network state vectors, anonymous tier. Airborne only (`on_ground=false`), non-null positions. `alt_m` is geometric altitude, or barometric when geometric is missing. Licence: OpenSky Network, non-commercial/research terms; credit "The OpenSky Network, https://opensky-network.org". |
+| `military.json` | 45 airborne aircraft | https://api.adsb.lol/v2/mil, plus https://opendata.adsb.fi/api/v2/mil (merged and de-duplicated by ICAO hex; adsb.lol wins) | 02:24 | Includes the `type` column (ICAO type code, e.g. C17, K35R). alt ft→m, gs kt→m/s. `country` is null because these feeds do not provide it. The count is low because the snapshot was taken at a quiet hour. A re-poll at 02:42 gave fewer (30 and 31 airborne). adsb.lol data is ODbL 1.0; adsb.fi open data. airplanes.live /v2/mil returned 403 and was not used. |
+| `tle.txt` | 15,928 satellites (3-line TLE) | https://celestrak.org/NORAD/elements/gp.php?GROUP=active&FORMAT=3le | 02:26 | CelesTrak "active" group. The FORMAT=tle request kept failing with connection resets after about 11 s through the proxy, while FORMAT=3le answered in 4 s. Element epochs range from day 264 to 293 of 2026. A descriptive User-Agent is required (as in server/providers/space/celestrak.js). Credit: CelesTrak / Dr T.S. Kelso. Data originates from 18th SDS / space-track.org. |
+| `tle_groups.json` | stations 17, starlink 10,651, gps-ops 32, geo 567, weather 72 | `gp.php?GROUP={stations,starlink,gps-ops,geo,weather}&FORMAT=tle` | 02:24–02:27 | `groups_norad`: NORAD ids per group, to join against `tle.txt` (columns 3–7 of line 1). `notable`: name→group for the first entries of each group (ISS (ZARYA), CSS (TIANHE), GOES, NOAA, GPS, …). |
+| `quakes.json` | 10,120 events | https://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/all_month.geojson | 02:24 (`t`=generated ms) | USGS ANSS ComCat. Covers 2026-09-18 02:26 to 2026-10-18 02:20 UTC, max M7.7. Sorted by time. Public domain (USGS). |
+| `fires.json` | 246,411 hotspots | https://firms.modaps.eosdis.nasa.gov/data/active_fire/suomi-npp-viirs-c2/csv/SUOMI_VIIRS_C2_Global_24h.csv (111,551); https://firms.modaps.eosdis.nasa.gov/data/active_fire/noaa-20-viirs-c2/csv/J1_VIIRS_C2_Global_24h.csv (118,991); https://firms.modaps.eosdis.nasa.gov/data/active_fire/modis-c6.1/csv/MODIS_C6_1_Global_24h.csv (15,869) | 02:24 | Rows are `[lon, lat, frp_MW, brightness_K]`. Brightness is VIIRS `bright_ti4` or MODIS `brightness`. Despite the "24h" names, the acquisitions run from 2026-10-16 00:11 to 2026-10-17 23:56 UTC. SNPP and NOAA-20 overlap, so the same fires appear twice. NASA FIRMS (LANCE); free use with credit "NASA FIRMS". |
+| `vessels.json` | 4,385 vessels | https://kystdatahuset.kystverket.no/ws/api/ais/realtime/geojson (Norway, 3,272 with a position); https://meri.digitraffic.fi/api/ais/v1/locations?from=<now-48h> + https://meri.digitraffic.fi/api/ais/v1/vessels for names (Finland/Baltic, 1,113 after de-duplication against Norway) | 02:28–02:29 | **Not global.** Coverage is the Norwegian coast and EEZ including Svalbard (Kystverket Kystdatahuset open API; NLOD licence) plus Finnish waters and the northern Baltic (Fintraffic Digitraffic; CC BY 4.0). Kystverket returns short trails, and the script uses the last vertex as the current position, checked against COG. `sog_kn`/`cog_deg` are null when AIS sends "not available". No keyless global AIS source was found. AISStream (the repo's source) needs a key, BarentsWatch needs OAuth (401), the Danish DMA host has an expired TLS certificate, and Kystverket's raw TCP NMEA feed cannot pass the HTTPS-only proxy. |
+| `wind.json` | 360×181 grid (65,160 cells) | https://noaa-gfs-bdp-pds.s3.amazonaws.com/gfs.20261017/18/atmos/gfs.t18z.pgrb2.1p00.f006 (byte ranges from its `.idx`, UGRD/VGRD at "10 m above ground") | 02:34 | NOAA GFS 1.0° run 2026-10-17 18Z, +6 h forecast, valid 2026-10-18 00Z. This is the same AWS Open Data bucket and `.idx` range approach as server/providers/wind/gfs.js, decoded with ecCodes (pip `eccodes`). The grid is re-indexed so `lo1=-180, la1=90, dx=dy=1`, row-major from north to south, m/s. The 00Z run of 10-18 was not yet published. Public domain (NOAA). |
+| `cables.json` | 1,948 polylines (732 cables) | https://www.submarinecablemap.com/api/v3/cable/cable-geo.json | 02:24 | Each LineString part is a separate polyline, rounded to 2 decimals. © TeleGeography, Submarine Cable Map (CC BY-SA 4.0); attribute TeleGeography. |
+| `coastline.json` | 1,429 lines, 60,392 vertices | https://raw.githubusercontent.com/nvkelso/natural-earth-vector/master/geojson/ne_50m_coastline.geojson | 02:24 | Natural Earth 1:50m coastline, rounded to 2 decimals with consecutive duplicate points removed. Public domain. |
+| `borders.json` | 288 rings | https://raw.githubusercontent.com/nvkelso/natural-earth-vector/master/geojson/ne_110m_admin_0_countries.geojson | 02:24 | Natural Earth 1:110m countries, each polygon ring as a line. Public domain. |
+| `cities.json` | 3,000 | https://raw.githubusercontent.com/nvkelso/natural-earth-vector/master/geojson/ne_10m_populated_places_simple.geojson | 02:24 | Top 3,000 by `pop_max`. Natural Earth, public domain. |
+| `airports.json` (bonus) | 5,280 (1,176 large, 4,104 medium) | https://davidmegginson.github.io/ourairports-data/airports.csv | 02:24 | OurAirports large and medium airports. `iata` falls back to the ICAO ident when there is no IATA code. `size` is L or M. Public domain. |
+| `radio.json` (bonus) | 12,983 stations | https://de1.api.radio-browser.info/json/stations/search?has_geo_info=true&hidebroken=true&limit=100000 | 02:40 | Radio Browser community directory (the repo's radio provider). Stations with geo coordinates only. Public domain / open. |
+| `bikes.json` (bonus) | 31,176 docks | 18 GBFS `station_information.json` feeds (Citi Bike, Divvy, Bay Wheels, Capital Bikeshare via gbfs.lyft.com; Bluebikes; Toronto, Barcelona, Madrid, São Paulo, Rio, Santiago, Bogotá via publicbikesystem.net; BIXI; Ecobici; Vélib'; Indego and LA Metro via bcycle; Oslo via urbansharing) + https://api.nextbike.net/maps/nextbike-live.json (all nextbike cities, 16,926 stations) | 02:41 | Per-system counts are in `systems`. Operator open-data terms apply (mostly GBFS open licences). |
+| `launch_sites.json` (bonus) | 249 pads | https://ll.thespacedevs.com/2.3.0/pads/?limit=100&mode=list (paged) | 02:42 | Launch Library 2 (The Space Devs), sorted by total launches. Free tier. |
+| `power_plants.json` (bonus) | 34,936 plants | https://raw.githubusercontent.com/wri/global-power-plant-database/master/output_database/global_power_plant_database.csv | 02:42 | WRI Global Power Plant Database v1.3 (static, 2021). CC BY 4.0. |
+
+Not produced: **military installations**. The repo's provider queries OSM Overpass by viewport only and rejects global requests. A global Overpass pull would be slow and against that design. **Datacenters**: the repo has no keyless source.
+
+## CCTV (`../cctv/`)
+
+`cctv/cam_001.jpg` … `cam_117.jpg`: 117 real frames, each fetched 2026-10-18 02:38:46–02:39:30 UTC and cover-cropped and resized to 640×360 (JPEG q88). `cctv/index.json` gives `file, name, city, country, lat, lon, source`, plus `fetched_utc`, `orig_size` and the frame `url`.
+
+About 235 frames were downloaded from 20 sources, and every one was reviewed on contact sheets. Placeholders were rejected: Caltrans "Temporarily Unavailable", Vegvesen "Kamera er midlertidig ute av drift", Tallinn "NB! ÜHENDUS KAAMERAGA PUUDUB", Barcelona "Interrupció temporal de la imatge", and one all-black King County frame. Frames whose average hash repeats within the set were also dropped as placeholders, as were frames under 320 px wide or with luminance mean ≤25 or std ≤15.
+
+Local time at capture: daylight in Sydney, NZ, Hong Kong and Singapore; evening or night in the Americas; pre-dawn night in Europe. The Hong Kong TD frames carry the department's own privacy-mask polygons.
+
+| Source | Frames | Country | Catalog endpoint (frames from) |
+|---|---|---|---|
+| Live Traffic NSW | 12 | Australia | https://data.livetraffic.com/cameras/traffic-cam.json (webcams.transport.nsw.gov.au) |
+| NZTA Waka Kotahi | 12 | New Zealand | https://trafficnz.info/service/traffic/rest/4/cameras/all (trafficnz.info/camera/*.jpg) |
+| HK Transport Department | 10 | Hong Kong | https://static.data.gov.hk/td/traffic-snapshot-images/code/Traffic_Camera_Locations_En.xml (tdcctv.data.one.gov.hk) |
+| LTA Singapore | 6 | Singapore | https://api.data.gov.sg/v1/transport/traffic-images (the feed listed only 8 cameras) |
+| NYC DOT | 9 | USA | https://webcams.nyctmc.org/api/cameras (…/{id}/image) |
+| Caltrans CCTV | 6 | USA | https://cwwp2.dot.ca.gov/data/d{4,7,11,3}/cctv/cctvStatusD0X.json |
+| WSDOT | 6 | USA | https://data.wsdot.wa.gov/travelcenter/Cameras.json (images.wsdot.wa.gov only) |
+| King County DOT | 3 | USA | ArcGIS TRAFFICCAMERA_POINT_2029 FeatureServer (info.kingcounty.gov) |
+| TxDOT ITS | 4 | USA | https://its.txdot.gov/its/DistrictIts/GetCctvStatusListByDistrict?districtCode=… (base64 JSON snapshot; Dallas and San Antonio worked, Houston and El Paso returned null) |
+| City of Austin | 4 | USA | https://data.austintexas.gov/api/views/b4k4-adkb/rows.json (cctv.austinmobility.io) |
+| DriveBC | 6 | Canada | https://www.drivebc.ca/api/webcams/ |
+| City of Toronto RESCU | 6 | Canada | https://opendata.toronto.ca/transportation/tmc/rescucameraimages/Data/tmcearthcameras.json |
+| City of Calgary | 4 | Canada | https://data.calgary.ca/resource/k7p9-kppz.json |
+| TfL JamCams | 8 | UK | https://api.tfl.gov.uk/Place/Type/JamCam (jamcams.tfl.gov.uk S3) |
+| Fintraffic Digitraffic | 4 | Finland | https://tie.digitraffic.fi/api/weathercam/v1/stations (weathercam.digitraffic.fi) |
+| Statens vegvesen | 4 | Norway | ogckart-sn1.atlas.vegvesen.no datex_3_1:CctvSimple (kamera.atlas.vegvesen.no) |
+| City of Tallinn | 3 | Estonia | repo config/cctv_sources.tallinn.json (ristmikud.tallinn.ee) |
+| Transpordiamet Tarktee | 3 | Estonia | tarktee.transpordiamet.ee DATEX2 roadCameraLocations + roadCameraImages |
+| Via Lietuva eismoinfo | 4 | Lithuania | https://eismoinfo.lt/eismoinfo-backend/camera-info-table + layer-static-features/VKR |
+| Servei Català de Trànsit catalog | 3 | Spain | https://www.gencat.cat/transit/opendata/cameres.xml (the 3 kept frames are Barcelona IMI cameras on www.bcn.cat; SCT's own mct.gencat.cat host would not answer over HTTPS) |
+
+Skipped: Ontario 511 (now answers "Invalid Key"), DelDOT (video only), Warendorf (http-only host, and the proxy allows HTTPS only).
+
+The frames are public agency imagery, used here under each agency's open-data or terms-of-use conditions. Credit the agency named in `source`. TfL: "Powered by TfL Open Data". NSW: © Transport for NSW. HK: © HKSAR Transport Department (data.gov.hk). Singapore: LTA via data.gov.sg (Singapore Open Data Licence). NZ: © NZ Transport Agency Waka Kotahi (CC BY 4.0).

intro-sequence/index.html

@@ -0,0 +1,26 @@
+<!doctype html>
+<html lang="en">
+<head>
+<meta charset="utf-8" />
+<title>God's Eye View — First Light</title>
+<style>
+  @font-face { font-family: 'JetBrains Mono'; font-weight: 400; src: url(node_modules/@fontsource/jetbrains-mono/files/jetbrains-mono-latin-400-normal.woff2) format('woff2'); }
+  @font-face { font-family: 'JetBrains Mono'; font-weight: 500; src: url(node_modules/@fontsource/jetbrains-mono/files/jetbrains-mono-latin-500-normal.woff2) format('woff2'); }
+  @font-face { font-family: 'Inter'; font-weight: 200; src: url(node_modules/@fontsource/inter/files/inter-latin-200-normal.woff2) format('woff2'); }
+  @font-face { font-family: 'Inter'; font-weight: 300; src: url(node_modules/@fontsource/inter/files/inter-latin-300-normal.woff2) format('woff2'); }
+  @font-face { font-family: 'Inter'; font-weight: 500; src: url(node_modules/@fontsource/inter/files/inter-latin-500-normal.woff2) format('woff2'); }
+  html, body { margin: 0; background: #000; overflow: hidden; }
+  canvas { display: block; }
+</style>
+<script type="importmap">
+{ "imports": {
+  "three": "./node_modules/three/build/three.module.js",
+  "satellite.js": "./node_modules/satellite.js/dist/satellite.es.js"
+} }
+</script>
+</head>
+<body>
+<canvas id="c"></canvas>
+<script type="module" src="src/main.js"></script>
+</body>
+</html>

intro-sequence/package-lock.json

@@ -0,0 +1,53 @@
+{
+  "name": "gev-intro-sequence",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "gev-intro-sequence",
+      "dependencies": {
+        "@fontsource/inter": "^5.1.1",
+        "@fontsource/jetbrains-mono": "^5.1.1",
+        "playwright-core": "^1.56.1",
+        "satellite.js": "^5.0.0",
+        "three": "^0.169.0"
+      }
+    },
+    "node_modules/@fontsource/inter": {
+      "version": "5.1.1",
+      "resolved": "https://registry.npmjs.org/@fontsource/inter/-/inter-5.1.1.tgz",
+      "integrity": "sha512-weN3E+rq0Xb3Z93VHJ+Rc7WOQX9ETJPTAJ+gDcaMHtjft67L58sfS65rAjC5tZUXQ2FdZ/V1/sSzCwZ6v05kJw==",
+      "license": "OFL-1.1"
+    },
+    "node_modules/@fontsource/jetbrains-mono": {
+      "version": "5.1.1",
+      "resolved": "https://registry.npmjs.org/@fontsource/jetbrains-mono/-/jetbrains-mono-5.1.1.tgz",
+      "integrity": "sha512-5rwvmdQQpXev4LlBX1P+7h2dguu6iwW/9Npjde4+DEq+HgpVJI/7QY8DI1NVVFdvLtXZNP+vO2L/5BQED6FUhA==",
+      "license": "OFL-1.1"
+    },
+    "node_modules/playwright-core": {
+      "version": "1.56.1",
+      "resolved": "https://registry.npmjs.org/playwright-core/-/playwright-core-1.56.1.tgz",
+      "integrity": "sha512-hutraynyn31F+Bifme+Ps9Vq59hKuUCz7H1kDOcBs+2oGguKkWTU50bBWrtz34OUWmIwpBTWDxaRPXrIXkgvmQ==",
+      "license": "Apache-2.0",
+      "bin": {
+        "playwright-core": "cli.js"
+      },
+      "engines": {
+        "node": ">=18"
+      }
+    },
+    "node_modules/satellite.js": {
+      "version": "5.0.0",
+      "resolved": "https://registry.npmjs.org/satellite.js/-/satellite.js-5.0.0.tgz",
+      "integrity": "sha512-ie3yiJ2LJAJIhVUKdYhgp7V0btXKAMImDjRnuaNfJGl8rjwP2HwVIh4HLFcpiXYEiYwXc5fqh5+yZqCe6KIwWw==",
+      "license": "MIT"
+    },
+    "node_modules/three": {
+      "version": "0.169.0",
+      "resolved": "https://registry.npmjs.org/three/-/three-0.169.0.tgz",
+      "integrity": "sha512-Ed906MA3dR4TS5riErd4QBsRGPcx+HBDX2O5yYE5GqJeFQTPU+M56Va/f/Oph9X7uZo3W3o4l2ZhBZ6f6qUv0w==",
+      "license": "MIT"
+    }
+  }
+}

intro-sequence/package.json

@@ -0,0 +1,14 @@
+{
+  "name": "gev-intro-sequence",
+  "private": true,
+  "type": "module",
+  "description": "God's Eye View: the intro sequence where the system comes online. Deterministic WebGL renderer + procedural score.",
+  "scripts": {},
+  "dependencies": {
+    "@fontsource/inter": "^5.1.1",
+    "@fontsource/jetbrains-mono": "^5.1.1",
+    "playwright-core": "^1.56.1",
+    "satellite.js": "^5.0.0",
+    "three": "^0.169.0"
+  }
+}

intro-sequence/src/city.js

@@ -0,0 +1,916 @@
+import * as THREE from 'three';
+import { mulberry32, clamp } from './timeline.js';
+
+// City scenes in a local ENU frame (data in metres, scene units in km;
+// three.js x = east, y = up, z = -north). One engine renders every location:
+// Esri ground, OSM buildings that rise as the scan passes, road ribbons that
+// carry modelled traffic coloured by congestion, cameras, aircraft, transit,
+// airports, restricted areas and terrain.
+
+const KM = 0.001;
+
+async function getJSON(p) {
+  try {
+    const r = await fetch(p);
+    return r.ok ? await r.json() : null;
+  } catch {
+    return null;
+  }
+}
+async function getBin(p) {
+  try {
+    const r = await fetch(p);
+    return r.ok ? await r.arrayBuffer() : null;
+  } catch {
+    return null;
+  }
+}
+function loadTex(p) {
+  return new Promise((res) =>
+    new THREE.TextureLoader().load(
+      p,
+      (t) => {
+        t.colorSpace = THREE.SRGBColorSpace;
+        t.anisotropy = 8;
+        res(t);
+      },
+      undefined,
+      () => res(null),
+    ),
+  );
+}
+
+export async function loadCity(slug) {
+  const base = `city/${slug}/`;
+  const [meta, buildings, roads, extra, cameras, air, transit, vehicles, aeroway, military, peaks, elevMeta, elev, ground] = await Promise.all([
+    getJSON(base + 'meta.json'),
+    getJSON(base + 'buildings.json'),
+    getJSON(base + 'roads.json'),
+    getJSON(base + 'extra.json'),
+    getJSON(base + 'cameras.json'),
+    getJSON(base + 'air.json'),
+    getJSON(base + 'transit.json'),
+    getJSON(base + 'vehicles.json'),
+    getJSON(base + 'aeroway.json'),
+    getJSON(base + 'military.json'),
+    getJSON(base + 'peaks.json'),
+    getJSON(base + 'elev_meta.json'),
+    getBin(base + 'elev.f32'),
+    loadTex(base + 'ground.jpg'),
+  ]);
+  return { slug, meta, buildings, roads, extra, cameras, air, transit, vehicles, aeroway, military, peaks, elevMeta, elev: elev ? new Float32Array(elev) : null, ground };
+}
+
+// ---------------------------------------------------------------- shared shader bits
+const HASH = /* glsl */ `
+  float h11(float n) { return fract(sin(n * 127.1) * 43758.5453); }
+  float h21(vec2 p) { return fract(sin(dot(p, vec2(127.1, 311.7))) * 43758.5453); }
+`;
+
+function congestionColor() {
+  return /* glsl */ `
+    vec3 congCol(float c) {
+      vec3 g = vec3(0.10, 1.00, 0.45);
+      vec3 y = vec3(1.00, 0.80, 0.10);
+      vec3 r = vec3(1.00, 0.16, 0.12);
+      return c < 0.5 ? mix(g, y, c * 2.0) : mix(y, r, (c - 0.5) * 2.0);
+    }
+  `;
+}
+
+// ---------------------------------------------------------------- ground
+function makeGround(d, half, elevGeo) {
+  const size = 2 * half * KM;
+  const geo = elevGeo || new THREE.PlaneGeometry(size, size, 1, 1).rotateX(-Math.PI / 2);
+  const mat = new THREE.ShaderMaterial({
+    uniforms: {
+      uTex: { value: d.ground },
+      uReveal: { value: 0 },
+      uT: { value: 0 },
+      uHalf: { value: half * KM },
+      uNight: { value: 0.55 },
+      uTerrain: { value: elevGeo ? 1 : 0 },
+      uScan: { value: -10 },
+      uFade: { value: 1 },
+    },
+    vertexShader: /* glsl */ `
+      attribute float aElev;
+      varying vec2 vUv;
+      varying vec3 vP;
+      varying float vElev;
+      varying vec3 vN;
+      void main() {
+        vUv = uv;
+        vP = position;
+        vElev = aElev;
+        vN = normal;
+        gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0);
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform sampler2D uTex;
+      uniform float uReveal, uT, uHalf, uNight, uTerrain, uScan, uFade;
+      varying vec2 vUv;
+      varying vec3 vP;
+      varying float vElev;
+      varying vec3 vN;
+      void main() {
+        vec3 img = texture2D(uTex, vUv).rgb;
+        float l = dot(img, vec3(0.3, 0.59, 0.11));
+        // night grade: cool, dim, contrasty — real pixels, but the city's lights do the talking
+        vec3 night = pow(mix(vec3(l), img, 0.35), vec3(1.7)) * vec3(0.5, 0.7, 0.95) * 0.56;
+        float r = length(vP.xz) / uHalf;
+        float rev = smoothstep(uReveal, uReveal - 0.08, r);
+        // tactical grid: 100 m, brighter every km
+        vec2 g = vP.xz * 1000.0;
+        vec2 fw = fwidth(g);
+        vec2 gl = abs(fract(g / 100.0 - 0.5) - 0.5) * 100.0 / fw;
+        float grid = 1.0 - smoothstep(0.0, 1.0, min(gl.x, gl.y));
+        vec2 gk = abs(fract(g / 1000.0 - 0.5) - 0.5) * 1000.0 / fw;
+        float gridK = 1.0 - smoothstep(0.0, 1.3, min(gk.x, gk.y));
+        vec3 col = night * rev;
+        col += vec3(0.0, 0.55, 0.7) * (grid * 0.05 + gridK * 0.14) * (0.4 + 0.6 * rev);
+        // the scan front
+        float ring = exp(-pow((r - uReveal) * 60.0, 2.0));
+        col += vec3(0.2, 0.9, 1.0) * ring * 0.6;
+        if (uTerrain > 0.5) {
+          // terrain: sunlit relief, 100 m contours, a LiDAR line sweeping across
+          vec3 L = normalize(vec3(-0.5, 0.7, 0.4));
+          float sh = clamp(dot(normalize(vN), L), 0.0, 1.0);
+          vec3 tg = pow(mix(vec3(l), img, 0.5), vec3(1.35));
+          col = tg * (0.08 + 0.62 * sh) * vec3(0.62, 0.78, 1.0) * rev;
+          float ce = vElev / 100.0;
+          float cw = fwidth(ce);
+          float cont = 1.0 - smoothstep(0.0, 1.2 * cw, abs(fract(ce - 0.5) - 0.5));
+          float major = 1.0 - smoothstep(0.0, 1.2 * fwidth(vElev / 500.0), abs(fract(vElev / 500.0 - 0.5) - 0.5));
+          col += vec3(0.1, 0.8, 1.0) * (cont * 0.16 + major * 0.5) * rev;
+          float sweep = exp(-pow((vP.x - uScan) * 18.0, 2.0));
+          col += vec3(0.4, 1.0, 1.0) * sweep * 0.9;
+          col += vec3(0.0, 0.6, 0.8) * smoothstep(uScan, uScan - 3.0, vP.x) * 0.03 * step(vP.x, uScan);
+        }
+        float edge = smoothstep(1.0, 0.82, max(abs(vP.x), abs(vP.z)) / uHalf);
+        gl_FragColor = vec4(col * edge * uFade, 1.0);
+      }
+    `,
+  });
+  // the ground never writes depth: it is the base layer, and road ribbons a
+  // metre above it would otherwise lose the depth test at city distances
+  if (!elevGeo) mat.depthWrite = false;
+  const mesh = new THREE.Mesh(geo, mat);
+  mesh.renderOrder = -1;
+  return mesh;
+}
+
+function makeTerrainGeo(d, half) {
+  const n = d.elevMeta?.size || 1024;
+  const seg = 384;
+  const size = 2 * half * KM;
+  const geo = new THREE.PlaneGeometry(size, size, seg, seg).rotateX(-Math.PI / 2);
+  const pos = geo.getAttribute('position');
+  const uv = geo.getAttribute('uv');
+  const el = new Float32Array(pos.count);
+  for (let i = 0; i < pos.count; i++) {
+    const u = uv.getX(i);
+    const v = uv.getY(i);
+    const px = Math.min(n - 1, Math.max(0, Math.round(u * (n - 1))));
+    const py = Math.min(n - 1, Math.max(0, Math.round((1 - v) * (n - 1))));
+    const h = d.elev[py * n + px];
+    el[i] = h;
+    pos.setY(i, h * KM);
+  }
+  geo.setAttribute('aElev', new THREE.BufferAttribute(el, 1));
+  geo.computeVertexNormals();
+  return geo;
+}
+
+// ---------------------------------------------------------------- buildings
+function makeBuildings(list) {
+  const P = [];
+  const UV = [];
+  const A = []; // height m, edge length m, dist km, rand
+  const idx = [];
+  let vi = 0;
+  const rnd = mulberry32(5);
+  const rings = [];
+  for (const b of list) {
+    const h = Math.max(4, Math.min(560, b[0] || 10));
+    const pts = [];
+    for (let i = 2; i < b.length - 1; i += 2) pts.push([b[i], b[i + 1]]);
+    if (pts.length < 3) continue;
+    let cx = 0;
+    let cy = 0;
+    for (const p of pts) {
+      cx += p[0];
+      cy += p[1];
+    }
+    cx /= pts.length;
+    cy /= pts.length;
+    const dist = Math.hypot(cx, cy) * KM;
+    const r = rnd();
+    // walls
+    for (let i = 0; i < pts.length; i++) {
+      const [x1, y1] = pts[i];
+      const [x2, y2] = pts[(i + 1) % pts.length];
+      const L = Math.hypot(x2 - x1, y2 - y1);
+      if (L < 0.3) continue;
+      P.push(x1 * KM, 0, -y1 * KM, x2 * KM, 0, -y2 * KM, x2 * KM, h * KM, -y2 * KM, x1 * KM, h * KM, -y1 * KM);
+      UV.push(0, 0, 1, 0, 1, 1, 0, 1);
+      for (let k = 0; k < 4; k++) A.push(h, L, dist, r);
+      idx.push(vi, vi + 1, vi + 2, vi, vi + 2, vi + 3);
+      vi += 4;
+    }
+    // roof
+    const contour = pts.map((p) => new THREE.Vector2(p[0], p[1]));
+    let tris = [];
+    try {
+      tris = THREE.ShapeUtils.triangulateShape(contour, []);
+    } catch {
+      tris = [];
+    }
+    const base = vi;
+    for (const p of pts) {
+      P.push(p[0] * KM, h * KM, -p[1] * KM);
+      UV.push(-1, 1); // u < 0 marks roof
+      A.push(h, 0, dist, r);
+      vi++;
+    }
+    for (const t of tris) idx.push(base + t[0], base + t[2], base + t[1]);
+    rings.push({ pts, h, dist });
+  }
+  const geo = new THREE.BufferGeometry();
+  geo.setAttribute('position', new THREE.Float32BufferAttribute(P, 3));
+  geo.setAttribute('uv', new THREE.Float32BufferAttribute(UV, 2));
+  geo.setAttribute('aB', new THREE.Float32BufferAttribute(A, 4));
+  geo.setIndex(vi > 65535 ? new THREE.Uint32BufferAttribute(idx, 1) : new THREE.Uint16BufferAttribute(idx, 1));
+  const mat = new THREE.ShaderMaterial({
+    uniforms: { uReveal: { value: 0 }, uT: { value: 0 }, uAlpha: { value: 1 }, uTint: { value: new THREE.Color('#38e8ff') } },
+    vertexShader: /* glsl */ `
+      attribute vec4 aB;
+      uniform float uReveal;
+      varying vec2 vUv;
+      varying vec4 vB;
+      varying vec3 vW;
+      varying float vRise;
+      void main() {
+        vUv = uv;
+        vB = aB;
+        float k = clamp((uReveal - aB.z) / 0.35, 0.0, 1.0);
+        float rise = 1.0 - pow(1.0 - k, 3.0);
+        vRise = k;
+        vec3 p = position;
+        p.y *= rise;
+        vec4 wp = modelMatrix * vec4(p, 1.0);
+        vW = wp.xyz;
+        gl_Position = projectionMatrix * viewMatrix * wp;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      ${HASH}
+      uniform float uReveal, uT, uAlpha;
+      uniform vec3 uTint;
+      varying vec2 vUv;
+      varying vec4 vB;
+      varying vec3 vW;
+      varying float vRise;
+      void main() {
+        if (vRise <= 0.0) discard;
+        float h = vB.x;
+        float L = vB.y;
+        bool roof = vUv.x < -0.5;
+        vec3 N = normalize(cross(dFdx(vW), dFdy(vW)));
+        float lit = 0.35 + 0.65 * abs(dot(N, normalize(vec3(0.4, 0.8, 0.3))));
+        float tall = smoothstep(30.0, 250.0, h);
+        vec3 base = mix(vec3(0.010, 0.016, 0.026), vec3(0.016, 0.032, 0.05), tall) * lit;
+        vec3 col = base;
+        float fresh = exp(-max(uReveal - vB.z, 0.0) * 5.0);
+        if (roof) {
+          col = base * 1.3 + uTint * 0.02;
+        } else {
+          // floors and windows
+          float fy = vUv.y * h / 3.4;
+          float fx = vUv.x * L / 3.2;
+          vec2 cell = floor(vec2(fx, fy));
+          vec2 f = fract(vec2(fx, fy));
+          float win = step(0.25, f.x) * step(f.x, 0.8) * step(0.3, f.y) * step(f.y, 0.75);
+          float on = step(0.9, h21(cell + vB.w * 91.0));
+          float warm = h21(cell * 1.7 + 3.0);
+          vec3 wc = mix(vec3(1.0, 0.75, 0.45), vec3(0.6, 0.9, 1.0), step(0.7, warm));
+          float flick = 0.85 + 0.15 * sin(uT * 2.0 + h21(cell) * 40.0);
+          col += wc * win * on * 0.32 * flick * smoothstep(0.0, 0.1, vRise);
+          // edges: crown line, vertical corners, base
+          float wy = fwidth(vUv.y);
+          float wx = fwidth(vUv.x);
+          float crown = 1.0 - smoothstep(0.0, wy * 1.5, 1.0 - vUv.y);
+          float corner = 1.0 - smoothstep(0.0, wx * 1.5, min(vUv.x, 1.0 - vUv.x));
+          col += uTint * (crown * (0.08 + tall * 0.9) + corner * (0.03 + tall * 0.12)) * (0.6 + fresh * 2.5);
+          // the scan passing up the facade as it rises
+          col += uTint * fresh * 0.25 * smoothstep(0.2, 1.0, vUv.y);
+        }
+        gl_FragColor = vec4(col * uAlpha, 1.0);
+      }
+    `,
+  });
+  const mesh = new THREE.Mesh(geo, mat);
+  mesh.frustumCulled = false;
+  return { mesh, count: rings.length, rings };
+}
+
+// ---------------------------------------------------------------- roads + traffic
+// Congestion is modelled, not measured: road class, distance to the core, and
+// a slow per-road noise. Labelled MODELED in the HUD.
+function makeRoads(list, half, { tint = null, inside = null, scale = 1 } = {}) {
+  const W = [34, 24, 20, 16, 11, 7];
+  const P = [];
+  const A = []; // arc m, side, cong, oneway
+  const B = []; // class, rnd, width
+  const idx = [];
+  let vi = 0;
+  const rnd = mulberry32(17);
+  let segs = 0;
+  for (const r of list) {
+    const cls = r[0];
+    const one = r[1] ? 1 : 0;
+    const pts = [];
+    for (let i = 3; i < r.length - 1; i += 2) pts.push([r[i], r[i + 1]]);
+    if (pts.length < 2) continue;
+    if (inside && !inside(pts[0][0], pts[0][1])) continue;
+    const w = W[cls] ?? 6;
+    const cx = pts[Math.floor(pts.length / 2)];
+    const core = Math.exp(-Math.hypot(cx[0], cx[1]) / (half * 0.55));
+    const base = [0.55, 0.5, 0.42, 0.35, 0.22, 0.3][cls] ?? 0.3;
+    const rr = rnd();
+    const cong = clamp(base * 0.55 + core * 0.55 + (rr - 0.5) * 0.95, 0, 1);
+    let arc = 0;
+    for (let i = 0; i < pts.length - 1; i++) {
+      const [x1, y1] = pts[i];
+      const [x2, y2] = pts[i + 1];
+      const L = Math.hypot(x2 - x1, y2 - y1);
+      if (L < 0.5) continue;
+      const nx = -(y2 - y1) / L;
+      const ny = (x2 - x1) / L;
+      const hw = w / 2;
+      const y = 0.6 + cls * 0.02;
+      const v = [
+        [x1 - nx * hw, y1 - ny * hw, -1, arc],
+        [x1 + nx * hw, y1 + ny * hw, 1, arc],
+        [x2 + nx * hw, y2 + ny * hw, 1, arc + L],
+        [x2 - nx * hw, y2 - ny * hw, -1, arc + L],
+      ];
+      for (const [x, yy, s, a] of v) {
+        P.push(x * KM, y * KM, -yy * KM);
+        A.push(a, s, cong, one);
+        B.push(cls, rr, w);
+      }
+      idx.push(vi, vi + 1, vi + 2, vi, vi + 2, vi + 3);
+      vi += 4;
+      arc += L;
+      segs++;
+    }
+  }
+  const geo = new THREE.BufferGeometry();
+  geo.setAttribute('position', new THREE.Float32BufferAttribute(P, 3));
+  geo.setAttribute('aA', new THREE.Float32BufferAttribute(A, 4));
+  geo.setAttribute('aC', new THREE.Float32BufferAttribute(B, 3));
+  geo.setIndex(new THREE.Uint32BufferAttribute(idx, 1));
+  const mat = new THREE.ShaderMaterial({
+    transparent: true,
+    side: THREE.DoubleSide,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    uniforms: {
+      uT: { value: 0 },
+      uReveal: { value: 0 },
+      uHalf: { value: half * KM },
+      uAlpha: { value: 1 },
+      uTint: { value: tint ? new THREE.Color(tint) : new THREE.Color(0, 0, 0) },
+      uUseTint: { value: tint ? 1 : 0 },
+      uScale: { value: scale },
+    },
+    vertexShader: /* glsl */ `
+      attribute vec4 aA;
+      attribute vec3 aC;
+      varying vec4 vA;
+      varying vec3 vC;
+      varying float vR;
+      void main() {
+        vA = aA;
+        vC = aC;
+        vR = length(position.xz);
+        gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0);
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      ${HASH}
+      ${congestionColor()}
+      uniform float uT, uReveal, uHalf, uAlpha, uUseTint, uScale;
+      uniform vec3 uTint;
+      varying vec4 vA;
+      varying vec3 vC;
+      varying float vR;
+      void main() {
+        float r = vR / uHalf;
+        float k = uReveal - r;
+        if (k < 0.0) discard;
+        float cong = vA.z;
+        float side = vA.y;
+        float dir = vA.w > 0.5 ? 1.0 : (side > 0.0 ? 1.0 : -1.0);
+        vec3 cc = mix(congCol(cong), uTint, uUseTint);
+        // ribbon cross-profile: soft edges, dark median
+        float a = abs(side);
+        float body = smoothstep(1.0, 0.7, a);
+        // cars: dashes flowing along each lane, slower and denser when jammed
+        float speed = mix(16.0, 2.5, cong) * 7.0 * uScale;
+        float spacing = mix(70.0, 14.0, cong);
+        float lane = vA.w > 0.5 ? 1.0 : smoothstep(0.05, 0.3, a) * smoothstep(0.98, 0.7, a);
+        float ph = (vA.x - dir * uT * speed) / spacing + vC.y * 13.0 + (side > 0.0 ? 0.37 : 0.0);
+        float fp = fract(ph);
+        float car = smoothstep(0.0, 0.04, fp) * (1.0 - smoothstep(0.08, 0.22, fp));
+        float present = step(0.25 + 0.5 * (1.0 - cong), h11(floor(ph) + vC.y * 77.0));
+        float head = car * present * lane;
+        vec3 carCol = dir > 0.0 ? vec3(1.0, 0.95, 0.85) : vec3(1.0, 0.25, 0.2);
+        vec3 col = cc * body * (0.2 + 0.12 * cong) + mix(cc, carCol, 0.22) * head * 1.25;
+        float fresh = exp(-k * 25.0);
+        col += cc * fresh * 0.8 * body;
+        gl_FragColor = vec4(col * uAlpha, 1.0);
+      }
+    `,
+  });
+  const mesh = new THREE.Mesh(geo, mat);
+  mesh.frustumCulled = false;
+  return { mesh, segs };
+}
+
+// ---------------------------------------------------------------- lines (generic, glowing)
+function makePolylines(lines, { color = '#38e8ff', y = 1, width = 0, alpha = 1, colors = null } = {}) {
+  const P = [];
+  const C = [];
+  const A = [];
+  for (let li = 0; li < lines.length; li++) {
+    const l = lines[li];
+    const col = new THREE.Color(colors ? colors[li] : color);
+    let arc = 0;
+    for (let i = 0; i < l.length - 1; i++) {
+      const [x1, y1, z1 = y] = l[i];
+      const [x2, y2, z2 = y] = l[i + 1];
+      const L = Math.hypot(x2 - x1, y2 - y1);
+      P.push(x1 * KM, z1 * KM, -y1 * KM, x2 * KM, z2 * KM, -y2 * KM);
+      C.push(col.r, col.g, col.b, col.r, col.g, col.b);
+      A.push(arc, arc + L);
+      arc += L;
+    }
+  }
+  const geo = new THREE.BufferGeometry();
+  geo.setAttribute('position', new THREE.Float32BufferAttribute(P, 3));
+  geo.setAttribute('color', new THREE.Float32BufferAttribute(C, 3));
+  geo.setAttribute('aArc', new THREE.Float32BufferAttribute(A, 1));
+  const mat = new THREE.ShaderMaterial({
+    transparent: true,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    vertexColors: true,
+    uniforms: { uT: { value: 0 }, uAlpha: { value: alpha }, uDraw: { value: 1e9 }, uPulse: { value: 0 } },
+    vertexShader: /* glsl */ `
+      attribute float aArc;
+      varying float vArc;
+      varying vec3 vCol;
+      void main() { vArc = aArc; vCol = color; gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0); }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform float uT, uAlpha, uDraw, uPulse;
+      varying float vArc;
+      varying vec3 vCol;
+      void main() {
+        if (vArc > uDraw) discard;
+        float p = uPulse > 0.0 ? pow(fract(vArc / 900.0 - uT * 0.8), 8.0) * 2.0 : 0.0;
+        gl_FragColor = vec4(vCol * (0.7 + p) * uAlpha, 1.0);
+      }
+    `,
+  });
+  return new THREE.LineSegments(geo, mat);
+}
+
+// glowing point sprites updated from the CPU
+function makePoints(n, { size = 6, color = '#ffffff' } = {}) {
+  const geo = new THREE.BufferGeometry();
+  const pos = new Float32Array(n * 3);
+  const col = new Float32Array(n * 3);
+  const sz = new Float32Array(n).fill(1);
+  const c = new THREE.Color(color);
+  for (let i = 0; i < n; i++) col.set([c.r, c.g, c.b], i * 3);
+  geo.setAttribute('position', new THREE.BufferAttribute(pos, 3));
+  geo.setAttribute('color', new THREE.BufferAttribute(col, 3));
+  geo.setAttribute('aS', new THREE.BufferAttribute(sz, 1));
+  const mat = new THREE.ShaderMaterial({
+    transparent: true,
+    depthWrite: false,
+    depthTest: false,
+    blending: THREE.AdditiveBlending,
+    vertexColors: true,
+    uniforms: { uSize: { value: size }, uAlpha: { value: 1 }, uPx: { value: 1 } },
+    vertexShader: /* glsl */ `
+      attribute float aS;
+      uniform float uSize, uPx;
+      varying vec3 vCol;
+      void main() { vCol = color; gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0); gl_PointSize = uSize * aS * uPx; }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform float uAlpha;
+      varying vec3 vCol;
+      void main() {
+        float r = length(gl_PointCoord - 0.5) * 2.0;
+        float a = smoothstep(1.0, 0.0, r);
+        float core = smoothstep(0.35, 0.0, r);
+        gl_FragColor = vec4((vCol * a * 0.8 + vec3(1.0) * core) * uAlpha, 1.0);
+      }
+    `,
+  });
+  const pts = new THREE.Points(geo, mat);
+  pts.frustumCulled = false;
+  return { pts, pos, col, sz, geo };
+}
+
+// ---------------------------------------------------------------- the engine
+export function buildCity(d, opts = {}) {
+  const half = d.meta?.half || 3500;
+  const scene = new THREE.Scene();
+  const group = new THREE.Group();
+  scene.add(group);
+  const out = { scene, d, half, labels: [], stats: {} };
+
+  const terrainGeo = d.elev ? makeTerrainGeo(d, half) : null;
+  const ground = makeGround(d, half, terrainGeo);
+  group.add(ground);
+  out.ground = ground;
+  if (d.elev) {
+    out.elevAt = (x, y) => {
+      const n = d.elevMeta?.size || 1024;
+      const px = Math.round(((x + half) / (2 * half)) * (n - 1));
+      const py = Math.round(((half - y) / (2 * half)) * (n - 1));
+      return d.elev[clamp(py, 0, n - 1) * n + clamp(px, 0, n - 1)] || 0;
+    };
+  }
+
+  if (d.buildings?.b?.length) {
+    const bl = makeBuildings(d.buildings.b);
+    group.add(bl.mesh);
+    out.buildings = bl;
+    out.stats.buildings = bl.count;
+  }
+
+  // military polygons: roads inside get the amber treatment
+  let insideMil = null;
+  if (d.military?.military?.length) {
+    const polys = d.military.military.map((m) => {
+      const pts = [];
+      for (let i = 1; i < m.length - 1; i += 2) pts.push([m[i], m[i + 1]]);
+      return { name: m[0], pts };
+    }).filter((p) => p.pts.length > 2 && p.pts.every(([x, y]) => Math.abs(x) < half * 1.35 && Math.abs(y) < half * 1.35));
+    // the reservation itself is bigger than the scene: keep what fits
+    out.milPolys = polys;
+    insideMil = (x, y) => polys.some((p) => pip(x, y, p.pts));
+  }
+
+  if (d.roads?.roads?.length) {
+    const rd = makeRoads(d.roads.roads, half);
+    group.add(rd.mesh);
+    out.roads = rd;
+    out.stats.roads = rd.segs;
+    if (insideMil) {
+      const conv = makeRoads(d.roads.roads, half, { tint: '#ffb547', inside: insideMil, scale: 0.6 });
+      conv.mesh.material.uniforms.uAlpha.value = 0.9;
+      group.add(conv.mesh);
+      out.convoy = conv;
+    }
+  }
+
+  // restricted areas: translucent curtains with scanning bands
+  if (out.milPolys) {
+    const P = [];
+    const U = [];
+    for (const p of out.milPolys) {
+      let arc = 0;
+      for (let i = 0; i < p.pts.length; i++) {
+        const [x1, y1] = p.pts[i];
+        const [x2, y2] = p.pts[(i + 1) % p.pts.length];
+        const L = Math.hypot(x2 - x1, y2 - y1);
+        const H = 0.35;
+        P.push(x1 * KM, 0, -y1 * KM, x2 * KM, 0, -y2 * KM, x2 * KM, H, -y2 * KM, x1 * KM, 0, -y1 * KM, x2 * KM, H, -y2 * KM, x1 * KM, H, -y1 * KM);
+        U.push(arc, 0, arc + L, 0, arc + L, 1, arc, 0, arc + L, 1, arc, 1);
+        arc += L;
+      }
+    }
+    const g = new THREE.BufferGeometry();
+    g.setAttribute('position', new THREE.Float32BufferAttribute(P, 3));
+    g.setAttribute('uv', new THREE.Float32BufferAttribute(U, 2));
+    const m = new THREE.ShaderMaterial({
+      transparent: true,
+      depthWrite: false,
+      side: THREE.DoubleSide,
+      blending: THREE.AdditiveBlending,
+      uniforms: { uT: { value: 0 }, uAlpha: { value: 0 } },
+      vertexShader: `varying vec2 vUv; void main(){ vUv = uv; gl_Position = projectionMatrix * modelViewMatrix * vec4(position,1.0); }`,
+      fragmentShader: /* glsl */ `
+        uniform float uT, uAlpha;
+        varying vec2 vUv;
+        void main() {
+          float band = pow(fract(vUv.y * 6.0 - uT * 0.6), 6.0);
+          float top = 1.0 - smoothstep(0.0, 0.04, 1.0 - vUv.y);
+          float fade = 1.0 - vUv.y;
+          float hatch = step(0.5, fract((vUv.x / 60.0 + vUv.y * 4.0)));
+          vec3 c = vec3(1.0, 0.62, 0.18) * (fade * 0.10 + band * 0.25 + top * 0.8 + hatch * fade * 0.03);
+          gl_FragColor = vec4(c * uAlpha, 1.0);
+        }
+      `,
+    });
+    out.curtain = new THREE.Mesh(g, m);
+    out.curtain.frustumCulled = false;
+    group.add(out.curtain);
+  }
+
+  // airport: runways, approach strobes, taxiways
+  const aw = d.aeroway || d.military;
+  if (aw?.runways?.length) {
+    const P = [];
+    const U = [];
+    const strobes = [];
+    for (const rw of aw.runways) {
+      const w = Math.max(30, rw[0] || 45);
+      const pts = [];
+      for (let i = 2; i < rw.length - 1; i += 2) pts.push([rw[i], rw[i + 1]]);
+      if (pts.length < 2) continue;
+      const [x1, y1] = pts[0];
+      const [x2, y2] = pts[pts.length - 1];
+      const L = Math.hypot(x2 - x1, y2 - y1);
+      const ux = (x2 - x1) / L;
+      const uy = (y2 - y1) / L;
+      const nx = -uy * w / 2;
+      const ny = ux * w / 2;
+      const q = [[x1 - nx, y1 - ny, 0, 0], [x1 + nx, y1 + ny, 1, 0], [x2 + nx, y2 + ny, 1, L], [x1 - nx, y1 - ny, 0, 0], [x2 + nx, y2 + ny, 1, L], [x2 - nx, y2 - ny, 0, L]];
+      for (const [x, y, s, a] of q) {
+        P.push(x * KM, 0.0012, -y * KM);
+        U.push(s, a);
+      }
+      // approach lighting: 900 m of strobes off each threshold
+      for (const [sx, sy, dx, dy] of [[x1, y1, -ux, -uy], [x2, y2, ux, uy]]) {
+        for (let k = 1; k <= 30; k++) strobes.push([sx + dx * k * 30, sy + dy * k * 30, k]);
+      }
+      out.labels.push({ kind: 'runway', x: (x1 + x2) / 2, y: (y1 + y2) / 2, text: `RWY ${rw[1] || ''}`.trim() });
+    }
+    const g = new THREE.BufferGeometry();
+    g.setAttribute('position', new THREE.Float32BufferAttribute(P, 3));
+    g.setAttribute('uv', new THREE.Float32BufferAttribute(U, 2));
+    const m = new THREE.ShaderMaterial({
+      transparent: true,
+      side: THREE.DoubleSide,
+      depthWrite: false,
+      blending: THREE.AdditiveBlending,
+      uniforms: { uT: { value: 0 }, uAlpha: { value: 1 } },
+      vertexShader: `varying vec2 vUv; void main(){ vUv = uv; gl_Position = projectionMatrix * modelViewMatrix * vec4(position,1.0); }`,
+      fragmentShader: /* glsl */ `
+        uniform float uT, uAlpha;
+        varying vec2 vUv;
+        void main() {
+          float edge = 1.0 - smoothstep(0.0, 0.06, min(vUv.x, 1.0 - vUv.x));
+          float cl = (1.0 - smoothstep(0.0, 0.03, abs(vUv.x - 0.5))) * step(0.5, fract(vUv.y / 60.0));
+          vec3 c = vec3(0.9, 0.95, 1.0) * (edge * 0.9 + cl * 0.7) + vec3(0.05, 0.08, 0.1);
+          gl_FragColor = vec4(c * uAlpha, 1.0);
+        }
+      `,
+    });
+    out.runways = new THREE.Mesh(g, m);
+    out.runways.frustumCulled = false;
+    group.add(out.runways);
+    out.strobes = makePoints(strobes.length, { size: 5, color: '#ffffff' });
+    strobes.forEach((s, i) => out.strobes.pos.set([s[0] * KM, 0.004, -s[1] * KM], i * 3));
+    out.strobeK = strobes.map((s) => s[2]);
+    out.strobes.geo.getAttribute('position').needsUpdate = true;
+    group.add(out.strobes.pts);
+  }
+  if (aw?.taxiways?.length) {
+    const lines = aw.taxiways.map((t) => {
+      const pts = [];
+      for (let i = 0; i < t.length - 1; i += 2) pts.push([t[i], t[i + 1], 1.2]);
+      return pts;
+    });
+    out.taxi = makePolylines(lines, { color: '#ffc04a', alpha: 0.75 });
+    group.add(out.taxi);
+  }
+  if (aw?.aprons?.length) {
+    const lines = aw.aprons.map((t) => {
+      const pts = [];
+      for (let i = 0; i < t.length - 1; i += 2) pts.push([t[i], t[i + 1], 1]);
+      if (pts.length) pts.push(pts[0]);
+      return pts;
+    });
+    out.aprons = makePolylines(lines, { color: '#2fd0ff', alpha: 0.4 });
+    group.add(out.aprons);
+  }
+
+  // transit: route-coloured lines with pulses, vehicles riding them
+  if (d.transit?.shapes?.length) {
+    const lines = [];
+    const colors = [];
+    out.shapes = [];
+    for (const s of d.transit.shapes) {
+      const rid = s[0];
+      const route = d.transit.routes[rid] || {};
+      const pts = [];
+      for (let i = 1; i < s.length - 1; i += 2) pts.push([s[i], s[i + 1], route.type === 3 ? 2 : 6]);
+      const col = route.color ? (route.color.startsWith('#') ? route.color : '#' + route.color) : '#38e8ff';
+      // subway and rail glow brighter than buses
+      lines.push(pts);
+      colors.push(route.type === 3 ? new THREE.Color(col).multiplyScalar(0.45).getStyle() : col);
+      out.shapes.push({ rid, pts, type: route.type });
+    }
+    out.transitLines = makePolylines(lines, { colors });
+    out.transitLines.material.uniforms.uPulse.value = 1;
+    group.add(out.transitLines);
+    out.stats.routes = Object.keys(d.transit.routes).length;
+  }
+  if (d.vehicles?.v?.length) {
+    const vs = d.vehicles.v;
+    out.veh = makePoints(vs.length, { size: 9 });
+    vs.forEach((v, i) => {
+      const r = d.transit?.routes?.[v[4]];
+      const c = new THREE.Color(r?.color ? (r.color.startsWith('#') ? r.color : '#' + r.color) : '#ffffff');
+      out.veh.col.set([c.r, c.g, c.b], i * 3);
+      out.veh.sz[i] = r?.type === 3 ? 0.65 : 1.2;
+    });
+    out.veh.geo.getAttribute('color').needsUpdate = true;
+    out.veh.geo.getAttribute('aS').needsUpdate = true;
+    group.add(out.veh.pts);
+    out.stats.vehicles = vs.length;
+  }
+
+  // street cameras: beams + base rings
+  if (d.cameras?.length) {
+    const lines = d.cameras.map((c) => [[c[0], c[1], 0], [c[0], c[1], 90]]);
+    out.camBeams = makePolylines(lines, { color: '#eafcff', alpha: 0.5 });
+    group.add(out.camBeams);
+    out.camPts = makePoints(d.cameras.length, { size: 7, color: '#bff6ff' });
+    d.cameras.forEach((c, i) => out.camPts.pos.set([c[0] * KM, 0.09, -c[1] * KM], i * 3));
+    out.camPts.geo.getAttribute('position').needsUpdate = true;
+    group.add(out.camPts.pts);
+    out.stats.cameras = d.cameras.length;
+  }
+
+  // aircraft (real ADS-B): glyphs + real track history
+  if (d.air?.a?.length) {
+    const a = d.air.a;
+    out.airPts = makePoints(a.length + 8, { size: 8, color: '#ffffff' });
+    a.forEach((p, i) => {
+      const heli = p[8] === 'A7' || /^(H|EC|AS|S7|S9|B06|B407|B429|A109|A119|A139|R44|R66|EC|H1|H6)/.test(p[7] || '');
+      const mil = /^(RCH|CNV|PAT|EVAC|TOPCT|HKY|SPAR|SAM)/.test(p[6] || '');
+      const c = new THREE.Color(heli ? '#7dffd6' : mil ? '#ffb547' : '#ffffff');
+      out.airPts.col.set([c.r, c.g, c.b], i * 3);
+      p.heli = heli;
+    });
+    out.airPts.geo.getAttribute('color').needsUpdate = true;
+    group.add(out.airPts.pts);
+    const tr = d.air.tracks || {};
+    const tl = Object.values(tr).filter((t) => t.length > 1).map((t) => t.map((q) => [q[0], q[1], q[2] * 1.5]));
+    if (tl.length) {
+      out.airTracks = makePolylines(tl.map((t) => t.filter((q) => Math.abs(q[0]) < half * 1.2 && Math.abs(q[1]) < half * 1.2)).filter((t) => t.length > 1), { color: '#9fe8ff', alpha: 0.3 });
+      group.add(out.airTracks);
+    }
+    out.stats.aircraft = a.length;
+    out.stats.helis = a.filter((p) => p.heli).length;
+  }
+
+  // modelled extras (labelled MODELED): helicopter tours, circuits
+  out.modeled = [];
+  if (opts.modeled) for (const m of opts.modeled) out.modeled.push(m);
+  if (out.modeled.length) {
+    out.modPts = makePoints(out.modeled.length, { size: 9, color: '#7dffd6' });
+    out.modeled.forEach((m, i) => {
+      const c = new THREE.Color(m.color || '#7dffd6');
+      out.modPts.col.set([c.r, c.g, c.b], i * 3);
+    });
+    out.modPts.geo.getAttribute('color').needsUpdate = true;
+    group.add(out.modPts.pts);
+    out.modTrails = makePolylines(out.modeled.map((m) => m.path.concat([m.path[0]])), { color: '#7dffd6', alpha: 0.25 });
+    out.modTrails.material.vertexColors = true;
+    group.add(out.modTrails);
+  }
+
+  // ---------------------------------------------------------------- per-frame
+  out.update = (lt, k, pxScale = 1) => {
+    // lt: seconds into this scene; k: 0..1 progress
+    const reveal = Math.min(1.6, 0.22 + lt * 1.05);
+    ground.material.uniforms.uReveal.value = reveal * 1.3;
+    ground.material.uniforms.uT.value = lt;
+    if (d.elev) ground.material.uniforms.uScan.value = -half * KM + ((lt * 0.35) % 1.2) * 2.4 * half * KM;
+    if (out.buildings) {
+      out.buildings.mesh.material.uniforms.uReveal.value = reveal * half * KM * 0.9;
+      out.buildings.mesh.material.uniforms.uT.value = lt;
+    }
+    if (out.roads) {
+      out.roads.mesh.material.uniforms.uReveal.value = reveal * 1.1;
+      out.roads.mesh.material.uniforms.uT.value = lt;
+    }
+    if (out.convoy) {
+      out.convoy.mesh.material.uniforms.uReveal.value = reveal * 1.1;
+      out.convoy.mesh.material.uniforms.uT.value = lt;
+    }
+    if (out.curtain) {
+      out.curtain.material.uniforms.uT.value = lt;
+      out.curtain.material.uniforms.uAlpha.value = clamp((lt - 0.6) * 1.5);
+    }
+    if (out.runways) out.runways.material.uniforms.uAlpha.value = clamp(lt * 1.2);
+    if (out.strobes) {
+      // the "rabbit": a pulse running in toward each threshold, twice a second
+      const ph = (lt * 2) % 1;
+      out.strobeK.forEach((kk, i) => (out.strobes.sz[i] = Math.abs((1 - kk / 30) - ph) < 0.05 ? 2.2 : 0.35));
+      out.strobes.geo.getAttribute('aS').needsUpdate = true;
+      out.strobes.pts.material.uniforms.uPx.value = pxScale;
+    }
+    if (out.transitLines) {
+      out.transitLines.material.uniforms.uT.value = lt;
+      out.transitLines.material.uniforms.uDraw.value = lt * 9000;
+    }
+    if (out.veh) {
+      const vs = d.vehicles.v;
+      for (let i = 0; i < vs.length; i++) {
+        const v = vs[i];
+        // dead-reckon along the reported bearing at the reported speed, sped up
+        const sp = Math.max(4, v[3] || 8) * 6;
+        const b = ((v[2] || 0) * Math.PI) / 180;
+        const x = v[0] + Math.sin(b) * sp * lt;
+        const y = v[1] + Math.cos(b) * sp * lt;
+        out.veh.pos.set([x * KM, 0.012, -y * KM], i * 3);
+      }
+      out.veh.geo.getAttribute('position').needsUpdate = true;
+      out.veh.pts.material.uniforms.uAlpha.value = clamp((lt - 0.8) * 2);
+      out.veh.pts.material.uniforms.uPx.value = pxScale;
+    }
+    if (out.camPts) {
+      out.camPts.pts.material.uniforms.uAlpha.value = clamp((lt - 0.9) * 2);
+      out.camBeams.material.uniforms.uAlpha.value = clamp((lt - 0.9) * 2) * 0.45;
+      out.camPts.pts.material.uniforms.uPx.value = pxScale;
+    }
+    if (out.airPts) {
+      const a = d.air.a;
+      for (let i = 0; i < a.length; i++) {
+        const p = a[i];
+        const b = ((p[3] || 0) * Math.PI) / 180;
+        const sp = (p[4] || 0) * 3;
+        const x = p[0] + Math.sin(b) * sp * lt;
+        const y = p[1] + Math.cos(b) * sp * lt;
+        const z = Math.max(0, (p[2] || 0) + (p[5] || 0) * 3 * lt) * 1.5;
+        out.airPts.pos.set([x * KM, z * KM + 0.004, -y * KM], i * 3);
+        p.now = [x, y, z];
+      }
+      out.airPts.geo.getAttribute('position').needsUpdate = true;
+      out.airPts.pts.material.uniforms.uAlpha.value = clamp((lt - 0.5) * 2);
+      out.airPts.pts.material.uniforms.uPx.value = pxScale;
+      if (out.airTracks) out.airTracks.material.uniforms.uAlpha.value = clamp((lt - 0.5) * 2) * 0.4;
+    }
+    if (out.modPts) {
+      out.modeled.forEach((m, i) => {
+        const p = pathAt(m.path, (lt * m.speed + m.phase) % 1);
+        out.modPts.pos.set([p[0] * KM, p[2] * KM, -p[1] * KM], i * 3);
+        m.now = p;
+      });
+      out.modPts.geo.getAttribute('position').needsUpdate = true;
+      out.modPts.pts.material.uniforms.uAlpha.value = clamp((lt - 0.7) * 2);
+      out.modPts.pts.material.uniforms.uPx.value = pxScale;
+      out.modTrails.material.uniforms.uAlpha.value = clamp((lt - 0.7) * 2) * 0.22;
+    }
+    if (out.taxi) out.taxi.material.uniforms.uAlpha.value = clamp((lt - 0.4) * 2) * 0.7;
+    if (out.aprons) out.aprons.material.uniforms.uAlpha.value = clamp((lt - 0.4) * 2) * 0.35;
+  };
+  return out;
+}
+
+function pathAt(path, f) {
+  const n = path.length;
+  const x = f * n;
+  const i = Math.floor(x) % n;
+  const j = (i + 1) % n;
+  const u = x - Math.floor(x);
+  const a = path[i];
+  const b = path[j];
+  return [a[0] + (b[0] - a[0]) * u, a[1] + (b[1] - a[1]) * u, (a[2] ?? 0) + ((b[2] ?? 0) - (a[2] ?? 0)) * u];
+}
+
+function pip(x, y, pts) {
+  let c = false;
+  for (let i = 0, j = pts.length - 1; i < pts.length; j = i++) {
+    const [xi, yi] = pts[i];
+    const [xj, yj] = pts[j];
+    if (yi > y !== yj > y && x < ((xj - xi) * (y - yi)) / (yj - yi) + xi) c = !c;
+  }
+  return c;
+}
+
+// An ellipse/loop path in metres, for modelled helicopter tours and circuits.
+export function loopPath(cx, cy, rx, ry, alt, rot = 0, n = 48) {
+  const out = [];
+  for (let i = 0; i < n; i++) {
+    const a = (i / n) * Math.PI * 2;
+    const x = Math.cos(a) * rx;
+    const y = Math.sin(a) * ry;
+    out.push([cx + x * Math.cos(rot) - y * Math.sin(rot), cy + x * Math.sin(rot) + y * Math.cos(rot), alt]);
+  }
+  return out;
+}

intro-sequence/src/geo.js

@@ -0,0 +1,72 @@
+// Geodesy for the film. Convention (matches the globe shader):
+//   x = cos(lat) cos(lon), y = sin(lat), z = -cos(lat) sin(lon)   (Y up, radius 1)
+export const D2R = Math.PI / 180;
+export const R2D = 180 / Math.PI;
+export const EARTH_KM = 6371;
+
+export function llToVec(lon, lat, r = 1, out = [0, 0, 0]) {
+  const la = lat * D2R;
+  const lo = lon * D2R;
+  const c = Math.cos(la);
+  out[0] = r * c * Math.cos(lo);
+  out[1] = r * Math.sin(la);
+  out[2] = -r * c * Math.sin(lo);
+  return out;
+}
+
+export function vecToLL(x, y, z) {
+  const r = Math.hypot(x, y, z);
+  return [Math.atan2(-z, x) * R2D, Math.asin(y / r) * R2D];
+}
+
+// Central angle in radians between two lon/lat points.
+export function angDist(lon1, lat1, lon2, lat2) {
+  const p1 = lat1 * D2R;
+  const p2 = lat2 * D2R;
+  const dp = p2 - p1;
+  const dl = (lon2 - lon1) * D2R;
+  const a = Math.sin(dp / 2) ** 2 + Math.cos(p1) * Math.cos(p2) * Math.sin(dl / 2) ** 2;
+  return 2 * Math.asin(Math.min(1, Math.sqrt(a)));
+}
+
+// Destination point given start, bearing (deg) and central angle (rad).
+export function destination(lon, lat, bearingDeg, ang) {
+  const p1 = lat * D2R;
+  const l1 = lon * D2R;
+  const b = bearingDeg * D2R;
+  const p2 = Math.asin(Math.sin(p1) * Math.cos(ang) + Math.cos(p1) * Math.sin(ang) * Math.cos(b));
+  const l2 = l1 + Math.atan2(Math.sin(b) * Math.sin(ang) * Math.cos(p1), Math.cos(ang) - Math.sin(p1) * Math.sin(p2));
+  return [((l2 * R2D + 540) % 360) - 180, p2 * R2D];
+}
+
+export function bearing(lon1, lat1, lon2, lat2) {
+  const p1 = lat1 * D2R;
+  const p2 = lat2 * D2R;
+  const dl = (lon2 - lon1) * D2R;
+  const y = Math.sin(dl) * Math.cos(p2);
+  const x = Math.cos(p1) * Math.sin(p2) - Math.sin(p1) * Math.cos(p2) * Math.cos(dl);
+  return (Math.atan2(y, x) * R2D + 360) % 360;
+}
+
+// Subsolar point (lon, lat) for a JS Date — NOAA low-precision solar position.
+export function subsolar(date) {
+  const jd = date.getTime() / 86400000 + 2440587.5;
+  const n = jd - 2451545.0;
+  const L = (280.46 + 0.9856474 * n) % 360;
+  const g = ((357.528 + 0.9856003 * n) % 360) * D2R;
+  const lambda = (L + 1.915 * Math.sin(g) + 0.02 * Math.sin(2 * g)) * D2R;
+  const eps = (23.439 - 0.0000004 * n) * D2R;
+  const decl = Math.asin(Math.sin(eps) * Math.sin(lambda));
+  const ra = Math.atan2(Math.cos(eps) * Math.sin(lambda), Math.cos(lambda));
+  const gmst = (280.46061837 + 360.98564736629 * n) % 360;
+  let lon = ra * R2D - gmst;
+  lon = ((lon + 540) % 360) - 180;
+  return [lon, decl * R2D];
+}
+
+export function fmtLat(lat, dp = 4) {
+  return `${Math.abs(lat).toFixed(dp)}°${lat >= 0 ? 'N' : 'S'}`;
+}
+export function fmtLon(lon, dp = 4) {
+  return `${Math.abs(lon).toFixed(dp)}°${lon >= 0 ? 'E' : 'W'}`;
+}

intro-sequence/src/globe.js

@@ -0,0 +1,296 @@
+import * as THREE from 'three';
+
+// The planet: one shader that walks the surface through every state the film
+// needs — dark substrate, the growth front lighting up night cities, quadtree
+// tiles indexing in with rising resolution, then the lit, living Earth.
+
+const COMMON = /* glsl */ `
+  #define PI 3.141592653589793
+  float hash3(vec3 p) {
+    p = fract(p * 0.3183099 + vec3(0.71, 0.113, 0.419));
+    p *= 17.0;
+    return fract(p.x * p.y * p.z * (p.x + p.y + p.z));
+  }
+  vec3 llDir(float lon, float lat) {
+    float c = cos(lat);
+    return vec3(c * cos(lon), sin(lat), -c * sin(lon));
+  }
+  // u wraps 1 -> 0 at the antimeridian; take derivatives from whichever of u or
+  // u+0.5 is continuous here so mip selection doesn't spike into a seam line
+  void seamGrad(vec2 uv, out vec2 gx, out vec2 gy) {
+    vec2 a = uv;
+    vec2 b = vec2(fract(uv.x + 0.5), uv.y);
+    vec2 ax = dFdx(a), ay = dFdy(a), bx = dFdx(b), by = dFdy(b);
+    gx = vec2(abs(ax.x) < abs(bx.x) ? ax.x : bx.x, ax.y);
+    gy = vec2(abs(ay.x) < abs(by.x) ? ay.x : by.x, ay.y);
+  }
+`;
+
+export function createGlobe({ dayTex, nightTex, cloudTex }) {
+  const uniforms = {
+    uDay: { value: dayTex },
+    uNight: { value: nightTex },
+    uTime: { value: 0 },
+    uSeed: { value: new THREE.Vector3(1, 0, 0) },
+    uSun: { value: new THREE.Vector3(1, 0, 0) },
+    uFront: { value: -1 }, // growth front, radians from the seed
+    uHolo: { value: 0 }, // substrate grid visibility
+    uLights: { value: 0 }, // night-light "neurons" during growth
+    uWave: { value: new THREE.Vector3(1e3, 1e3, 1e3) },
+    uWaveSpread: { value: 2.6 },
+    uImagery: { value: 0 }, // forces imagery fully on (after indexing)
+    uLit: { value: 0 }, // 0 = flat imagery, 1 = real sun lighting
+    uTexel: { value: new THREE.Vector2(1 / 8192, 1 / 4096) },
+    uGridAmt: { value: 1 },
+    uTint: { value: 0 }, // cyan analysis tint on the whole surface
+    uDim: { value: 1 },
+  };
+
+  const mat = new THREE.ShaderMaterial({
+    uniforms,
+    vertexShader: /* glsl */ `
+      varying vec3 vObj;
+      varying vec3 vWorldN;
+      varying vec3 vView;
+      void main() {
+        vObj = position;
+        vec4 wp = modelMatrix * vec4(position, 1.0);
+        vWorldN = normalize(mat3(modelMatrix) * position);
+        vView = normalize(cameraPosition - wp.xyz);
+        gl_Position = projectionMatrix * viewMatrix * wp;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      ${COMMON}
+      uniform sampler2D uDay, uNight;
+      uniform float uTime, uFront, uHolo, uLights, uWaveSpread, uImagery, uLit, uGridAmt, uTint, uDim;
+      uniform vec3 uSeed, uSun, uWave;
+      uniform vec2 uTexel;
+      varying vec3 vObj;
+      varying vec3 vWorldN;
+      varying vec3 vView;
+
+      float mercY(float lat) {
+        lat = clamp(lat, -1.4844, 1.4844);
+        return 0.5 - log(tan(PI * 0.25 + lat * 0.5)) / (2.0 * PI);
+      }
+      float invMercY(float my) {
+        return atan(sinh(PI * (1.0 - 2.0 * my)));
+      }
+
+      // Per-level quadtree state at this fragment.
+      // returns x = phase since this tile revealed, y = edge line (0..1)
+      vec2 tileState(float z, float waveT, vec2 uv, float my, float jitter) {
+        float n = exp2(z);
+        vec2 tc = vec2(uv.x * n, my * n);
+        vec2 ti = floor(tc);
+        vec2 f = fract(tc);
+        float lonc = ((ti.x + 0.5) / n) * 2.0 * PI - PI;
+        float latc = invMercY((ti.y + 0.5) / n);
+        float d = acos(clamp(dot(uSeed, llDir(lonc, latc)), -1.0, 1.0));
+        float tRev = waveT + d / PI * uWaveSpread + hash3(vec3(ti, z)) * jitter;
+        vec2 tcb = vec2(fract(uv.x + 0.5) * n, tc.y);
+        vec2 w = vec2(min(fwidth(tc.x), fwidth(tcb.x)), fwidth(tc.y));
+        vec2 e = min(f, 1.0 - f) / max(w, vec2(1e-5));
+        float line = 1.0 - smoothstep(0.0, 1.25, min(e.x, e.y));
+        return vec2(uTime - tRev, line);
+      }
+
+      void main() {
+        vec3 n = normalize(vObj);
+        float lat = asin(clamp(n.y, -1.0, 1.0));
+        float lon = atan(-n.z, n.x);
+        vec2 uv = vec2(lon / (2.0 * PI) + 0.5, lat / PI + 0.5);
+        float my = mercY(lat);
+        vec3 N = normalize(vWorldN);
+        vec3 V = normalize(vView);
+        float dSeed = acos(clamp(dot(n, uSeed), -1.0, 1.0));
+
+        // ---------- substrate (pre-imagery)
+        float gLat = abs(fract(lat * 180.0 / PI / 10.0 + 0.5) - 0.5) * 10.0;
+        float gLon = abs(fract(lon * 180.0 / PI / 10.0 + 0.5) - 0.5) * 10.0 * cos(lat);
+        float gw = fwidth(lat * 180.0 / PI) * 1.2;
+        float gwl = min(fwidth(lon), fwidth(mod(lon + 2.0 * PI, 2.0 * PI))) * 180.0 / PI * 1.2 * cos(lat);
+        float grid = max(1.0 - smoothstep(0.0, gw, gLat), 1.0 - smoothstep(0.0, max(gwl, 1e-4), gLon));
+        float behind = smoothstep(uFront + 0.02, uFront - 0.10, dSeed);
+        vec3 base = vec3(0.0018, 0.0035, 0.006) * behind;
+        vec3 holo = base + vec3(0.0, 0.35, 0.42) * grid * 0.10 * uHolo * behind;
+        // growth front: a thin bright ring with a soft wake
+        float ring = exp(-pow((dSeed - uFront) * 55.0, 2.0)) * step(0.0, uFront);
+        float wake = exp(-max(uFront - dSeed, 0.0) * 6.0) * behind;
+        holo += vec3(0.1, 0.85, 1.0) * (ring * 0.55 + wake * 0.035) * uHolo;
+
+        // real night lights, colonised by the front: the "neurons"
+        vec2 gx, gy;
+        seamGrad(uv, gx, gy);
+        float nl = textureGrad(uNight, uv, gx, gy).r;
+        float nlc = pow(max(nl - 0.06, 0.0) * 1.07, 1.7);
+        float fresh = exp(-max(uFront - dSeed, 0.0) * 3.0);
+        holo += mix(vec3(0.55, 0.95, 1.0), vec3(1.0), fresh) * nlc * (1.2 + fresh * 2.5) * behind * uLights;
+
+        // ---------- quadtree indexing
+        vec2 s3 = tileState(3.0, uWave.x, uv, my, 0.35);
+        vec2 s4 = tileState(4.0, uWave.y, uv, my, 0.30);
+        vec2 s5 = tileState(5.0, uWave.z, uv, my, 0.25);
+        float reveal = max(smoothstep(0.05, 0.42, s3.x), uImagery);
+        // resolution climbs as each finer wave passes
+        float bias = mix(4.5, 0.0, max(smoothstep(0.0, 0.5, s5.x), uImagery));
+        bias = min(bias, mix(4.5, 2.2, smoothstep(0.0, 0.5, s4.x)));
+        float bs = exp2(bias);
+        vec2 bgx = gx * bs, bgy = gy * bs;
+        vec3 day = textureGrad(uDay, uv, bgx, bgy).rgb;
+
+        // analysis edges (luminance gradient) — only while a tile is being indexed
+        float ph0 = s3.x;
+        float edgeAmt0 = step(0.0, ph0) * exp(-max(ph0 - 0.1, 0.0) * 2.2) * (1.0 - uImagery);
+        float edge = 0.0;
+        if (edgeAmt0 > 0.002) {
+          float l0 = dot(textureGrad(uDay, uv + vec2(uTexel.x, 0.0), bgx, bgy).rgb, vec3(0.3, 0.59, 0.11));
+          float l1 = dot(textureGrad(uDay, uv - vec2(uTexel.x, 0.0), bgx, bgy).rgb, vec3(0.3, 0.59, 0.11));
+          float l2 = dot(textureGrad(uDay, uv + vec2(0.0, uTexel.y), bgx, bgy).rgb, vec3(0.3, 0.59, 0.11));
+          float l3 = dot(textureGrad(uDay, uv - vec2(0.0, uTexel.y), bgx, bgy).rgb, vec3(0.3, 0.59, 0.11));
+          edge = clamp(length(vec2(l0 - l1, l2 - l3)) * 9.0, 0.0, 1.0);
+        }
+
+        // ---------- lighting
+        float sd = dot(n, uSun);
+        float dayF = smoothstep(-0.10, 0.20, sd);
+        vec3 lit = day * (0.035 + 1.25 * pow(max(sd, 0.0), 0.75)) * dayF + day * 0.012;
+        float ocean = smoothstep(0.015, 0.06, day.b - day.r) * (1.0 - smoothstep(0.08, 0.25, dot(day, vec3(0.33))));
+        vec3 Hh = normalize(normalize(mat3(1.0) * uSun) + V);
+        float graze = smoothstep(0.15, 0.5, dot(N, V));
+        float spec = (pow(max(dot(N, Hh), 0.0), 240.0) * 0.4 + pow(max(dot(N, Hh), 0.0), 30.0) * 0.03) * ocean * dayF * graze;
+        vec3 cityGlow = vec3(1.0, 0.72, 0.42) * pow(nl, 1.9) * 1.6 * (1.0 - dayF);
+        float fres = pow(1.0 - max(dot(N, V), 0.0), 3.0);
+        vec3 haze = vec3(0.25, 0.5, 1.0) * fres * (0.15 + 0.85 * dayF) * 0.7;
+        vec3 earthLit = lit + vec3(1.0, 0.92, 0.8) * spec + cityGlow + haze;
+        vec3 earthFlat = day * 0.6;
+        vec3 earth = mix(earthFlat, earthLit, uLit);
+
+        // reveal treatment: flash, edges, then settle
+        float ph = s3.x;
+        float flash = step(0.0, ph) * exp(-max(ph, 0.0) * 9.0);
+        float edgeAmt = step(0.0, ph) * exp(-max(ph - 0.1, 0.0) * 2.2) * (1.0 - uImagery);
+        vec3 surf = mix(holo, earth, reveal);
+        surf += vec3(0.0, 0.8, 1.0) * edge * edgeAmt * 0.9;
+        surf += vec3(0.6, 0.95, 1.0) * flash * 0.10 * (1.0 - uImagery);
+        surf = mix(surf, vec3(dot(surf, vec3(0.3, 0.59, 0.11))) * vec3(0.4, 1.0, 1.15), uTint);
+
+        // tile edges: faint before, bright at their own wave, then gone
+        float g3 = s3.y * (step(ph, 0.0) * 0.18 * uHolo * behind + step(0.0, ph) * exp(-max(ph, 0.0) * 1.6) * 1.3);
+        float g4 = s4.y * step(0.0, s4.x) * exp(-max(s4.x, 0.0) * 2.0) * 0.9;
+        float g5 = s5.y * step(0.0, s5.x) * exp(-max(s5.x, 0.0) * 2.6) * 0.7;
+        surf += vec3(0.25, 0.9, 1.0) * max(g3, max(g4, g5)) * uGridAmt;
+
+        gl_FragColor = vec4(surf * uDim, 1.0);
+      }
+    `,
+  });
+
+  const geo = new THREE.SphereGeometry(1, 384, 192);
+  const mesh = new THREE.Mesh(geo, mat);
+
+  // Clouds — real GIBS-derived opacity, lit by the same sun.
+  const cloudU = {
+    uClouds: { value: cloudTex },
+    uSun: uniforms.uSun,
+    uAmt: { value: 0 },
+    uTime: uniforms.uTime,
+  };
+  const cloudMat = new THREE.ShaderMaterial({
+    uniforms: cloudU,
+    transparent: true,
+    depthWrite: false,
+    vertexShader: /* glsl */ `
+      varying vec3 vObj;
+      varying vec3 vN;
+      varying vec3 vView;
+      void main() {
+        vObj = position;
+        vec4 wp = modelMatrix * vec4(position, 1.0);
+        vN = normalize(mat3(modelMatrix) * position);
+        vView = normalize(cameraPosition - wp.xyz);
+        gl_Position = projectionMatrix * viewMatrix * wp;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      #define PI 3.141592653589793
+      uniform sampler2D uClouds;
+      uniform vec3 uSun;
+      uniform float uAmt, uTime;
+      varying vec3 vObj;
+      varying vec3 vN;
+      varying vec3 vView;
+      void main() {
+        vec3 n = normalize(vObj);
+        float lat = asin(clamp(n.y, -1.0, 1.0));
+        float lon = atan(-n.z, n.x) - uTime * 0.0015;
+        vec2 uv = vec2(fract(lon / (2.0 * PI) + 0.5), lat / PI + 0.5);
+        vec2 ua = uv, ub = vec2(fract(uv.x + 0.5), uv.y);
+        vec2 ax = dFdx(ua), ay = dFdy(ua), bx = dFdx(ub), by = dFdy(ub);
+        vec2 gx = vec2(abs(ax.x) < abs(bx.x) ? ax.x : bx.x, ax.y);
+        vec2 gy = vec2(abs(ay.x) < abs(by.x) ? ay.x : by.x, ay.y);
+        float c = textureGrad(uClouds, uv, gx, gy).r;
+        c = smoothstep(0.08, 0.85, c);
+        float sd = dot(n, uSun);
+        float dayF = smoothstep(-0.12, 0.25, sd);
+        vec3 col = vec3(1.0, 0.98, 0.95) * (0.02 + 1.1 * dayF * (0.35 + 0.65 * max(sd, 0.0)));
+        float edge = pow(1.0 - max(dot(normalize(vN), normalize(vView)), 0.0), 2.0);
+        gl_FragColor = vec4(col, c * uAmt * (0.92 - edge * 0.4));
+      }
+    `,
+  });
+  const clouds = new THREE.Mesh(new THREE.SphereGeometry(1.0065, 256, 128), cloudMat);
+
+  // Atmosphere shell — limb glow, warm-to-blue at the terminator.
+  const atmoU = { uSun: uniforms.uSun, uAmt: { value: 0 }, uCyan: { value: 0 } };
+  const atmoMat = new THREE.ShaderMaterial({
+    uniforms: atmoU,
+    side: THREE.BackSide,
+    transparent: true,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    vertexShader: /* glsl */ `
+      varying vec3 vN;
+      varying vec3 vWP;
+      void main() {
+        vec4 wp = modelMatrix * vec4(position, 1.0);
+        vWP = wp.xyz;
+        vN = normalize(mat3(modelMatrix) * position);
+        gl_Position = projectionMatrix * viewMatrix * wp;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform vec3 uSun;
+      uniform float uAmt, uCyan;
+      varying vec3 vN;
+      varying vec3 vWP;
+      void main() {
+        vec3 V = normalize(cameraPosition - vWP);
+        vec3 N = normalize(vN);
+        // distance of this view ray from the planet centre, in radii
+        vec3 ro = cameraPosition;
+        vec3 rd = -V;
+        float b = dot(ro, rd);
+        float h = length(ro - b * rd);
+        float shell = 1.065;
+        float t = clamp((shell - h) / (shell - 1.0), 0.0, 1.0);
+        float glow = pow(t, 2.6) * (1.0 - smoothstep(0.985, 1.0, t) * 0.0);
+        if (h < 1.0) glow *= 0.0;
+        // light side vs dark side of the limb
+        vec3 limbP = normalize(ro + rd * b);
+        float sd = dot(limbP, uSun);
+        float lit = smoothstep(-0.35, 0.4, sd);
+        vec3 col = mix(vec3(0.02, 0.08, 0.14), vec3(0.35, 0.62, 1.0), lit);
+        col += vec3(1.0, 0.45, 0.2) * exp(-pow(sd * 6.0, 2.0)) * 0.35;
+        col = mix(col, vec3(0.1, 0.9, 1.0) * 0.8, uCyan);
+        gl_FragColor = vec4(col * glow * uAmt * 1.05, 1.0);
+      }
+    `,
+  });
+  const atmo = new THREE.Mesh(new THREE.SphereGeometry(1.065, 128, 64), atmoMat);
+
+  const group = new THREE.Group();
+  group.add(mesh, clouds, atmo);
+  return { group, mesh, uniforms, cloudU, atmoU };
+}

intro-sequence/src/layers.js

@@ -0,0 +1,512 @@
+import * as THREE from 'three';
+import { llToVec, D2R, EARTH_KM } from './geo.js';
+import { mulberry32 } from './timeline.js';
+
+// Point and particle layers for the live feeds. Every layer exposes
+// `update(t, ctx)`; reveal timing and motion are pure functions of film time.
+
+const GC = /* glsl */ `
+  vec3 llDir(float lon, float lat) {
+    float c = cos(lat);
+    return vec3(c * cos(lon), sin(lat), -c * sin(lon));
+  }
+  // great-circle destination: start (lon,lat) rad, bearing rad, distance rad
+  vec2 gcDest(vec2 ll, float b, float d) {
+    float lat2 = asin(sin(ll.y) * cos(d) + cos(ll.y) * sin(d) * cos(b));
+    float lon2 = ll.x + atan(sin(b) * sin(d) * cos(ll.y), cos(d) - sin(ll.y) * sin(lat2));
+    return vec2(lon2, lat2);
+  }
+`;
+
+// Moving contacts (aircraft, vessels): heads as points, trails as segments.
+// rows: [lon, lat, alt_m, track_deg, vel_ms]
+export function createMovers(rows, { color, trailColor, size = 2.2, altScale = 8, trail = 0.010, revealSpread = 1.4, seed = 1, gain = 1 }) {
+  const rnd = mulberry32(seed);
+  const n = rows.length;
+  const ll = new Float32Array(n * 2);
+  const hv = new Float32Array(n * 2);
+  const alt = new Float32Array(n);
+  const rr = new Float32Array(n);
+  rows.forEach((r, i) => {
+    ll[i * 2] = r[0] * D2R;
+    ll[i * 2 + 1] = r[1] * D2R;
+    hv[i * 2] = (r[3] || 0) * D2R;
+    hv[i * 2 + 1] = (r[4] || 0) / (EARTH_KM * 1000); // rad per second
+    alt[i] = 1 + ((r[2] || 0) / (EARTH_KM * 1000)) * altScale + 0.0015;
+    rr[i] = rnd();
+  });
+
+  const uniforms = {
+    uSim: { value: 0 }, // simulated seconds since the feed went live
+    uReveal: { value: 0 }, // 0..1 + spread
+    uAlpha: { value: 0 },
+    uGain: { value: gain },
+    uPx: { value: 1 },
+    uSize: { value: size },
+    uTrail: { value: trail },
+    uColor: { value: new THREE.Color(color) },
+    uTrailColor: { value: new THREE.Color(trailColor || color) },
+    uSpread: { value: revealSpread },
+  };
+  const vs = (isTrail) => /* glsl */ `
+    ${GC}
+    attribute vec2 aLL;
+    attribute vec2 aHV;
+    attribute float aAlt;
+    attribute float aR;
+    ${isTrail ? 'attribute float aEnd;' : ''}
+    uniform float uSim, uReveal, uPx, uSize, uTrail, uSpread;
+    varying float vA;
+    varying float vFacing;
+    void main() {
+      float d = aHV.y * uSim;
+      ${isTrail ? 'd -= aEnd * max(uTrail, aHV.y * 40.0);' : ''}
+      vec2 p = gcDest(aLL, aHV.x, d);
+      vec3 pos = llDir(p.x, p.y) * aAlt;
+      vec4 wp = modelMatrix * vec4(pos, 1.0);
+      vFacing = dot(normalize(wp.xyz), normalize(cameraPosition - wp.xyz));
+      float rv = clamp((uReveal - aR * uSpread) * 6.0, 0.0, 1.0);
+      vA = rv ${isTrail ? '* (1.0 - aEnd)' : ''};
+      gl_Position = projectionMatrix * viewMatrix * wp;
+      ${isTrail ? '' : 'gl_PointSize = uSize * uPx * (1.0 + 2.5 * exp(-(uReveal - aR * uSpread) * 10.0) * step(0.0, uReveal - aR * uSpread));'}
+    }
+  `;
+  const fs = (isTrail) => /* glsl */ `
+    uniform vec3 ${isTrail ? 'uTrailColor' : 'uColor'};
+    uniform float uAlpha, uGain;
+    varying float vA;
+    varying float vFacing;
+    void main() {
+      float back = smoothstep(-0.02, 0.12, vFacing);
+      ${
+        isTrail
+          ? 'gl_FragColor = vec4(uTrailColor * vA * uAlpha * uGain * back * 0.9, 1.0);'
+          : `vec2 c = gl_PointCoord - 0.5;
+             float r = length(c);
+             float disc = smoothstep(0.5, 0.15, r);
+             if (vA * back <= 0.001) discard;
+             gl_FragColor = vec4(uColor * disc * vA * uAlpha * uGain * back, 1.0);`
+      }
+    }
+  `;
+  const mk = (isTrail) =>
+    new THREE.ShaderMaterial({
+      uniforms,
+      transparent: true,
+      depthWrite: false,
+      blending: THREE.AdditiveBlending,
+      vertexShader: vs(isTrail),
+      fragmentShader: fs(isTrail),
+    });
+
+  const gp = new THREE.BufferGeometry();
+  gp.setAttribute('position', new THREE.BufferAttribute(new Float32Array(n * 3), 3));
+  gp.setAttribute('aLL', new THREE.BufferAttribute(ll, 2));
+  gp.setAttribute('aHV', new THREE.BufferAttribute(hv, 2));
+  gp.setAttribute('aAlt', new THREE.BufferAttribute(alt, 1));
+  gp.setAttribute('aR', new THREE.BufferAttribute(rr, 1));
+  gp.boundingSphere = new THREE.Sphere(new THREE.Vector3(), 2);
+  const heads = new THREE.Points(gp, mk(false));
+
+  // trails: two vertices per contact, aEnd 0 (head) / 1 (tail)
+  const dup = (src, k) => {
+    const out = new Float32Array(src.length * 2);
+    for (let i = 0; i < src.length / k; i++)
+      for (let j = 0; j < k; j++) {
+        out[i * 2 * k + j] = src[i * k + j];
+        out[i * 2 * k + k + j] = src[i * k + j];
+      }
+    return out;
+  };
+  const gt = new THREE.BufferGeometry();
+  gt.setAttribute('position', new THREE.BufferAttribute(new Float32Array(n * 6), 3));
+  gt.setAttribute('aLL', new THREE.BufferAttribute(dup(ll, 2), 2));
+  gt.setAttribute('aHV', new THREE.BufferAttribute(dup(hv, 2), 2));
+  gt.setAttribute('aAlt', new THREE.BufferAttribute(dup(alt, 1), 1));
+  gt.setAttribute('aR', new THREE.BufferAttribute(dup(rr, 1), 1));
+  const ends = new Float32Array(n * 2);
+  for (let i = 0; i < n; i++) ends[i * 2 + 1] = 1;
+  gt.setAttribute('aEnd', new THREE.BufferAttribute(ends, 1));
+  gt.boundingSphere = new THREE.Sphere(new THREE.Vector3(), 2);
+  const trails = new THREE.LineSegments(gt, mk(true));
+
+  const group = new THREE.Group();
+  group.add(trails, heads);
+  return { group, uniforms, count: n };
+}
+
+// Static or pulsing point events (fires, quakes, cities, cameras).
+// rows: [lon, lat, weight]
+export function createEvents(rows, { color, size = 3, mode = 'flicker', r = 1.002, spread = 1.2, seed = 3, gain = 1, weightFn = (w) => w }) {
+  const rnd = mulberry32(seed);
+  const n = rows.length;
+  const pos = new Float32Array(n * 3);
+  const w = new Float32Array(n);
+  const rr = new Float32Array(n);
+  const v = [0, 0, 0];
+  rows.forEach((row, i) => {
+    llToVec(row[0], row[1], r, v);
+    pos.set(v, i * 3);
+    w[i] = weightFn(row[2] ?? 1);
+    rr[i] = rnd();
+  });
+  const uniforms = {
+    uT: { value: 0 },
+    uReveal: { value: 0 },
+    uAlpha: { value: 0 },
+    uGain: { value: gain },
+    uPx: { value: 1 },
+    uSize: { value: size },
+    uColor: { value: new THREE.Color(color) },
+    uSpread: { value: spread },
+  };
+  const g = new THREE.BufferGeometry();
+  g.setAttribute('position', new THREE.BufferAttribute(pos, 3));
+  g.setAttribute('aW', new THREE.BufferAttribute(w, 1));
+  g.setAttribute('aR', new THREE.BufferAttribute(rr, 1));
+  const ringMode = mode === 'ring';
+  const m = new THREE.ShaderMaterial({
+    uniforms,
+    transparent: true,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    vertexShader: /* glsl */ `
+      attribute float aW;
+      attribute float aR;
+      uniform float uT, uReveal, uPx, uSize, uSpread;
+      varying float vA;
+      varying float vPh;
+      varying float vW;
+      varying float vFacing;
+      void main() {
+        vec4 wp = modelMatrix * vec4(position, 1.0);
+        vFacing = dot(normalize(wp.xyz), normalize(cameraPosition - wp.xyz));
+        float k = uReveal - aR * uSpread;
+        vA = clamp(k * 5.0, 0.0, 1.0);
+        vPh = k;
+        vW = aW;
+        gl_Position = projectionMatrix * viewMatrix * wp;
+        ${
+          ringMode
+            ? 'gl_PointSize = uSize * uPx * (0.6 + aW) * 9.0;'
+            : 'gl_PointSize = uSize * uPx * (0.7 + aW) * (1.0 + 3.0 * exp(-max(k, 0.0) * 8.0) * step(0.0, k));'
+        }
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform vec3 uColor;
+      uniform float uT, uAlpha, uGain;
+      varying float vA;
+      varying float vPh;
+      varying float vW;
+      varying float vFacing;
+      void main() {
+        float back = smoothstep(-0.02, 0.12, vFacing);
+        if (vA * back <= 0.001) discard;
+        vec2 c = gl_PointCoord - 0.5;
+        float r = length(c) * 2.0;
+        ${
+          ringMode
+            ? `float ph = fract(vPh * 0.55 + vW * 0.37);
+               float ringR = ph;
+               float ring = exp(-pow((r - ringR) * 14.0, 2.0)) * (1.0 - ph);
+               float core = smoothstep(0.16, 0.0, r);
+               float first = exp(-max(vPh, 0.0) * 3.0);
+               float a = ring * (0.8 + first) + core * 1.4;`
+            : `float flick = 0.65 + 0.35 * sin(uT * (9.0 + vW * 7.0) + vW * 91.0);
+               float a = smoothstep(1.0, 0.0, r) * smoothstep(1.0, 0.25, r) * 1.5 * flick;`
+        }
+        gl_FragColor = vec4(uColor * a * vA * uAlpha * uGain * back, 1.0);
+      }
+    `,
+  });
+  const pts = new THREE.Points(g, m);
+  return { group: pts, uniforms, count: n };
+}
+
+// Satellites: positions arrive from satellite.js each frame.
+export function createSatellites(count, { color = '#d6d0ff', size = 1.7 } = {}) {
+  const pos = new Float32Array(count * 3);
+  const rr = new Float32Array(count);
+  const kind = new Float32Array(count);
+  const rnd = mulberry32(11);
+  for (let i = 0; i < count; i++) rr[i] = rnd();
+  const g = new THREE.BufferGeometry();
+  const pa = new THREE.BufferAttribute(pos, 3);
+  pa.setUsage(THREE.DynamicDrawUsage);
+  g.setAttribute('position', pa);
+  g.setAttribute('aR', new THREE.BufferAttribute(rr, 1));
+  g.setAttribute('aK', new THREE.BufferAttribute(kind, 1));
+  g.boundingSphere = new THREE.Sphere(new THREE.Vector3(), 20);
+  const uniforms = {
+    uReveal: { value: 0 },
+    uAlpha: { value: 0 },
+    uPx: { value: 1 },
+    uSize: { value: size },
+    uColor: { value: new THREE.Color(color) },
+  };
+  const m = new THREE.ShaderMaterial({
+    uniforms,
+    transparent: true,
+    depthWrite: false,
+    depthTest: true,
+    blending: THREE.AdditiveBlending,
+    vertexShader: /* glsl */ `
+      attribute float aR;
+      attribute float aK;
+      uniform float uReveal, uPx, uSize;
+      varying float vA;
+      varying float vK;
+      void main() {
+        float k = uReveal - aR * 1.3;
+        vA = clamp(k * 5.0, 0.0, 1.0);
+        vK = aK;
+        gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0);
+        float big = aK > 0.5 ? 1.6 : 1.0;
+        gl_PointSize = uSize * uPx * big * (1.0 + 3.0 * exp(-max(k, 0.0) * 9.0) * step(0.0, k));
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform vec3 uColor;
+      uniform float uAlpha;
+      varying float vA;
+      varying float vK;
+      void main() {
+        if (vA <= 0.001) discard;
+        float r = length(gl_PointCoord - 0.5) * 2.0;
+        float a = smoothstep(1.0, 0.1, r);
+        vec3 c = mix(uColor * 0.75, vec3(0.75, 1.0, 1.0) * 1.4, step(0.5, vK));
+        gl_FragColor = vec4(c * a * vA * uAlpha, 1.0);
+      }
+    `,
+  });
+  const pts = new THREE.Points(g, m);
+  return { group: pts, uniforms, positions: pos, attr: pa, kind, count };
+}
+
+// Orbit rings for a handful of notable objects.
+export function createOrbitRings(paths, color = '#bfb6ff') {
+  const pos = [];
+  const u = [];
+  for (const path of paths) {
+    for (let i = 0; i < path.length - 1; i++) {
+      pos.push(...path[i], ...path[i + 1]);
+      u.push(i / (path.length - 1), (i + 1) / (path.length - 1));
+    }
+  }
+  const g = new THREE.BufferGeometry();
+  g.setAttribute('position', new THREE.Float32BufferAttribute(pos, 3));
+  g.setAttribute('aU', new THREE.Float32BufferAttribute(u, 1));
+  const m = new THREE.ShaderMaterial({
+    transparent: true,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    uniforms: { uDraw: { value: 0 }, uAlpha: { value: 0 }, uColor: { value: new THREE.Color(color) } },
+    vertexShader: /* glsl */ `
+      attribute float aU;
+      varying float vU;
+      varying float vNear;
+      void main() {
+        vU = aU;
+        vec4 mv = modelViewMatrix * vec4(position, 1.0);
+        vNear = smoothstep(1.2, 4.5, -mv.z);
+        gl_Position = projectionMatrix * mv;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform float uDraw, uAlpha;
+      uniform vec3 uColor;
+      varying float vU;
+      varying float vNear;
+      void main() {
+        float k = uDraw - vU;
+        if (k < 0.0) discard;
+        float hot = exp(-k * 30.0) * 2.0;
+        gl_FragColor = vec4((uColor * 0.4 + vec3(1.0) * hot) * uAlpha * vNear, 1.0);
+      }
+    `,
+  });
+  return new THREE.LineSegments(g, m);
+}
+
+// Wind: particles advected through a real GFS u/v field, drawn as fading trails.
+export function createWind(field, { count = 7000, trailLen = 14, seed = 21 } = {}) {
+  const { nx, ny, lo1, la1, dx, dy, u, v } = field;
+  const sample = (lon, lat) => {
+    let x = (((lon - lo1) % 360) + 360) % 360 / dx;
+    let y = (la1 - lat) / dy;
+    const x0 = Math.floor(x);
+    const y0 = Math.max(0, Math.min(ny - 2, Math.floor(y)));
+    const fx = x - x0;
+    const fy = Math.max(0, Math.min(1, y - y0));
+    const i00 = y0 * nx + (x0 % nx);
+    const i10 = y0 * nx + ((x0 + 1) % nx);
+    const i01 = (y0 + 1) * nx + (x0 % nx);
+    const i11 = (y0 + 1) * nx + ((x0 + 1) % nx);
+    const bl = (arr) => (arr[i00] * (1 - fx) + arr[i10] * fx) * (1 - fy) + (arr[i01] * (1 - fx) + arr[i11] * fx) * fy;
+    return [bl(u), bl(v)];
+  };
+  const SEGS = trailLen - 1;
+  const pos = new Float32Array(count * SEGS * 2 * 3);
+  const alpha = new Float32Array(count * SEGS * 2);
+  const g = new THREE.BufferGeometry();
+  const pa = new THREE.BufferAttribute(pos, 3);
+  pa.setUsage(THREE.DynamicDrawUsage);
+  const aa = new THREE.BufferAttribute(alpha, 1);
+  aa.setUsage(THREE.DynamicDrawUsage);
+  g.setAttribute('position', pa);
+  g.setAttribute('aA', aa);
+  g.boundingSphere = new THREE.Sphere(new THREE.Vector3(), 2);
+  const uniforms = { uAlpha: { value: 0 }, uColor: { value: new THREE.Color('#a6dcff') } };
+  const m = new THREE.ShaderMaterial({
+    uniforms,
+    transparent: true,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    vertexShader: /* glsl */ `
+      attribute float aA;
+      varying float vA;
+      varying float vFacing;
+      void main() {
+        vA = aA;
+        vec4 wp = modelMatrix * vec4(position, 1.0);
+        vFacing = dot(normalize(wp.xyz), normalize(cameraPosition - wp.xyz));
+        gl_Position = projectionMatrix * viewMatrix * wp;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform vec3 uColor;
+      uniform float uAlpha;
+      varying float vA;
+      varying float vFacing;
+      void main() {
+        float back = smoothstep(0.0, 0.15, vFacing);
+        gl_FragColor = vec4(uColor * vA * uAlpha * back, 1.0);
+      }
+    `,
+  });
+  const lines = new THREE.LineSegments(g, m);
+
+  // particle state
+  const P = { lon: new Float32Array(count), lat: new Float32Array(count), age: new Float32Array(count), life: new Float32Array(count), spd: new Float32Array(count) };
+  const hist = new Float32Array(count * trailLen * 2);
+  let rnd;
+  let simT = -1;
+  const spawn = (i) => {
+    const lon = rnd() * 360 - 180;
+    const lat = Math.asin(rnd() * 2 - 1) * (180 / Math.PI) * 0.92;
+    P.lon[i] = lon;
+    P.lat[i] = lat;
+    P.age[i] = 0;
+    P.life[i] = 1.2 + rnd() * 2.2;
+    for (let k = 0; k < trailLen; k++) {
+      hist[(i * trailLen + k) * 2] = lon;
+      hist[(i * trailLen + k) * 2 + 1] = lat;
+    }
+  };
+  const reset = () => {
+    rnd = mulberry32(seed);
+    for (let i = 0; i < count; i++) {
+      spawn(i);
+      P.age[i] = rnd() * P.life[i];
+    }
+    simT = 0;
+  };
+  const DT = 1 / 30;
+  const K = 0.85; // deg per (m/s) per second of film — visual speed
+  const step = () => {
+    for (let i = 0; i < count; i++) {
+      const [uu, vv] = sample(P.lon[i], P.lat[i]);
+      P.spd[i] = Math.hypot(uu, vv);
+      const c = Math.max(0.2, Math.cos(P.lat[i] * D2R));
+      P.lon[i] += (uu * K * DT) / c;
+      P.lat[i] += vv * K * DT;
+      if (P.lon[i] > 180) P.lon[i] -= 360;
+      if (P.lon[i] < -180) P.lon[i] += 360;
+      P.age[i] += DT;
+      const base = i * trailLen * 2;
+      hist.copyWithin(base + 2, base, base + (trailLen - 1) * 2);
+      hist[base] = P.lon[i];
+      hist[base + 1] = P.lat[i];
+      if (P.age[i] > P.life[i] || Math.abs(P.lat[i]) > 84) spawn(i);
+    }
+    simT += DT;
+  };
+  const a = [0, 0, 0];
+  const b = [0, 0, 0];
+  function update(tSinceStart) {
+    if (simT < 0 || tSinceStart < simT - 1e-6) reset();
+    while (simT < tSinceStart) step();
+    let o = 0;
+    let q = 0;
+    for (let i = 0; i < count; i++) {
+      const base = i * trailLen * 2;
+      const life = P.age[i] / P.life[i];
+      const fade = Math.min(1, life * 5) * Math.min(1, (1 - life) * 4);
+      const sp = Math.min(1, P.spd[i] / 18);
+      for (let k = 0; k < SEGS; k++) {
+        const lo1 = hist[base + k * 2];
+        const la1 = hist[base + k * 2 + 1];
+        const lo2 = hist[base + (k + 1) * 2];
+        const la2 = hist[base + (k + 1) * 2 + 1];
+        const jump = Math.abs(lo2 - lo1) > 90;
+        llToVec(lo1, la1, 1.004, a);
+        llToVec(jump ? lo1 : lo2, jump ? la1 : la2, 1.004, b);
+        pos[o++] = a[0]; pos[o++] = a[1]; pos[o++] = a[2];
+        pos[o++] = b[0]; pos[o++] = b[1]; pos[o++] = b[2];
+        const f1 = (1 - k / SEGS) * fade * (0.25 + sp);
+        const f2 = (1 - (k + 1) / SEGS) * fade * (0.25 + sp);
+        alpha[q++] = f1;
+        alpha[q++] = f2;
+      }
+    }
+    pa.needsUpdate = true;
+    aa.needsUpdate = true;
+  }
+  return { group: lines, uniforms, update, count };
+}
+
+export function createStars(n = 2600, seed = 77) {
+  const rnd = mulberry32(seed);
+  const pos = new Float32Array(n * 3);
+  const mag = new Float32Array(n);
+  for (let i = 0; i < n; i++) {
+    const z = rnd() * 2 - 1;
+    const t = rnd() * Math.PI * 2;
+    const s = Math.sqrt(1 - z * z);
+    pos[i * 3] = 400 * s * Math.cos(t);
+    pos[i * 3 + 1] = 400 * z;
+    pos[i * 3 + 2] = 400 * s * Math.sin(t);
+    mag[i] = Math.pow(rnd(), 6);
+  }
+  const g = new THREE.BufferGeometry();
+  g.setAttribute('position', new THREE.BufferAttribute(pos, 3));
+  g.setAttribute('aM', new THREE.BufferAttribute(mag, 1));
+  const uniforms = { uAlpha: { value: 0 }, uPx: { value: 1 } };
+  const m = new THREE.ShaderMaterial({
+    uniforms,
+    transparent: true,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    vertexShader: /* glsl */ `
+      attribute float aM;
+      uniform float uPx;
+      varying float vM;
+      void main() {
+        vM = aM;
+        gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0);
+        gl_PointSize = (1.0 + aM * 2.2) * uPx;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform float uAlpha;
+      varying float vM;
+      void main() {
+        float r = length(gl_PointCoord - 0.5) * 2.0;
+        float a = smoothstep(1.0, 0.0, r);
+        gl_FragColor = vec4(vec3(0.8, 0.9, 1.0) * a * (0.12 + vM * 0.9) * uAlpha, 1.0);
+      }
+    `,
+  });
+  return { group: new THREE.Points(g, m), uniforms };
+}

intro-sequence/src/lines.js

@@ -0,0 +1,323 @@
+import * as THREE from 'three';
+import { llToVec, angDist, destination, bearing, D2R } from './geo.js';
+import { mulberry32 } from './timeline.js';
+
+// Line layers that reveal along a scalar "arrival" attribute (radians from the
+// seed, or arc length), with a hot tip at the front and a configurable wake.
+export function frontLineMaterial({ color, alpha = 1, after = 0.25, tip = 3.0, decay = 4.0, additive = true }) {
+  return new THREE.ShaderMaterial({
+    transparent: true,
+    depthWrite: false,
+    depthTest: true,
+    blending: additive ? THREE.AdditiveBlending : THREE.NormalBlending,
+    uniforms: {
+      uColor: { value: new THREE.Color(color) },
+      uFront: { value: -1 },
+      uAlpha: { value: alpha },
+      uAfter: { value: after },
+      uTip: { value: tip },
+      uDecay: { value: decay },
+      uFadeBack: { value: 1 },
+    },
+    vertexShader: /* glsl */ `
+      attribute float aDist;
+      varying float vDist;
+      varying float vFacing;
+      void main() {
+        vDist = aDist;
+        vec4 wp = modelMatrix * vec4(position, 1.0);
+        vec3 n = normalize(wp.xyz);
+        vFacing = dot(n, normalize(cameraPosition - wp.xyz));
+        gl_Position = projectionMatrix * viewMatrix * wp;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform vec3 uColor;
+      uniform float uFront, uAlpha, uAfter, uTip, uDecay, uFadeBack;
+      varying float vDist;
+      varying float vFacing;
+      void main() {
+        float behind = uFront - vDist;
+        if (behind < 0.0) discard;
+        float a = uAfter + (1.0 - uAfter) * exp(-behind * uDecay);
+        float hot = exp(-behind * 60.0) * uTip;
+        float back = mix(1.0, smoothstep(-0.15, 0.25, vFacing), uFadeBack);
+        vec3 c = uColor * (a + hot) + vec3(1.0) * hot * 0.6;
+        gl_FragColor = vec4(c * uAlpha * back, 1.0);
+      }
+    `,
+  });
+}
+
+function segmentsFromPolylines(lines, r, distFn) {
+  const pos = [];
+  const dist = [];
+  const a = [0, 0, 0];
+  const b = [0, 0, 0];
+  for (const line of lines) {
+    for (let i = 0; i < line.length - 1; i++) {
+      const [lo1, la1] = line[i];
+      const [lo2, la2] = line[i + 1];
+      if (Math.abs(lo2 - lo1) > 180) continue; // antimeridian jump
+      llToVec(lo1, la1, r, a);
+      llToVec(lo2, la2, r, b);
+      pos.push(...a, ...b);
+      dist.push(distFn(lo1, la1, i, line), distFn(lo2, la2, i + 1, line));
+    }
+  }
+  const g = new THREE.BufferGeometry();
+  g.setAttribute('position', new THREE.Float32BufferAttribute(pos, 3));
+  g.setAttribute('aDist', new THREE.Float32BufferAttribute(dist, 1));
+  return g;
+}
+
+export function createCoastline(lines, seedLL, color = '#3ff0ff') {
+  const g = segmentsFromPolylines(lines, 1.0008, (lo, la) => angDist(seedLL[0], seedLL[1], lo, la));
+  const m = frontLineMaterial({ color, after: 0.32, tip: 5.0, decay: 3.0 });
+  return new THREE.LineSegments(g, m);
+}
+
+export function createBorders(lines, seedLL, color = '#1aa6c4') {
+  const g = segmentsFromPolylines(lines, 1.0006, (lo, la) => angDist(seedLL[0], seedLL[1], lo, la));
+  const m = frontLineMaterial({ color, after: 0.18, tip: 1.5, decay: 3.0 });
+  return new THREE.LineSegments(g, m);
+}
+
+// Mycelium: a branching random walk out from the seed. Each vertex carries its
+// path length so the network visibly *grows* rather than appearing.
+export function createMycelium(seedLL, { primaries = 22, maxSegs = 60000, seed = 7 } = {}) {
+  const rnd = mulberry32(seed);
+  const pos = [];
+  const dist = [];
+  const a = [0, 0, 0];
+  const b = [0, 0, 0];
+  const stack = [];
+  for (let i = 0; i < primaries; i++) {
+    stack.push({ lon: seedLL[0], lat: seedLL[1], brg: (360 * i) / primaries + rnd() * 12, len: 0, depth: 0, life: 150 + rnd() * 120 });
+  }
+  let segs = 0;
+  while (stack.length && segs < maxSegs) {
+    const br = stack.pop();
+    let { lon, lat, brg, len } = br;
+    const step = (0.5 + rnd() * 0.5) * D2R * (br.depth === 0 ? 1.2 : 0.9);
+    for (let s = 0; s < br.life && segs < maxSegs; s++) {
+      // outward bias keeps the culture expanding rather than knotting
+      const away = (bearing(lon, lat, seedLL[0], seedLL[1]) + 180) % 360;
+      let diff = ((away - brg + 540) % 360) - 180;
+      brg += diff * 0.04 + (rnd() - 0.5) * 26;
+      const [nl, nt] = destination(lon, lat, brg, step);
+      if (Math.abs(nl - lon) < 180) {
+        llToVec(lon, lat, 1.0012, a);
+        llToVec(nl, nt, 1.0012, b);
+        pos.push(...a, ...b);
+        dist.push(len * 0.82, (len + step) * 0.82);
+        segs++;
+      }
+      lon = nl;
+      lat = nt;
+      len += step;
+      if (len > Math.PI * 1.05) break;
+      const pBranch = br.depth < 5 ? 0.07 : 0.02;
+      if (rnd() < pBranch) {
+        stack.push({ lon, lat, brg: brg + (rnd() < 0.5 ? -1 : 1) * (22 + rnd() * 45), len, depth: br.depth + 1, life: (br.life - s) * (0.35 + rnd() * 0.5) });
+      }
+    }
+  }
+  const g = new THREE.BufferGeometry();
+  g.setAttribute('position', new THREE.Float32BufferAttribute(pos, 3));
+  g.setAttribute('aDist', new THREE.Float32BufferAttribute(dist, 1));
+  const m = frontLineMaterial({ color: '#2fe8ff', after: 0.07, tip: 4.0, decay: 2.2 });
+  const obj = new THREE.LineSegments(g, m);
+  obj.userData.segments = segs;
+  return obj;
+}
+
+// Subsea cables: drawn on, then light pulses ride them.
+export function createCables(cables) {
+  const pos = [];
+  const arc = [];
+  const rnd = [];
+  const a = [0, 0, 0];
+  const b = [0, 0, 0];
+  const r = mulberry32(99);
+  for (const line of cables) {
+    let L = 0;
+    const off = r();
+    for (let i = 0; i < line.length - 1; i++) {
+      const [lo1, la1] = line[i];
+      const [lo2, la2] = line[i + 1];
+      if (Math.abs(lo2 - lo1) > 180) continue;
+      const d = angDist(lo1, la1, lo2, la2);
+      llToVec(lo1, la1, 1.0015, a);
+      llToVec(lo2, la2, 1.0015, b);
+      pos.push(...a, ...b);
+      arc.push(L, L + d);
+      rnd.push(off, off);
+      L += d;
+    }
+  }
+  const g = new THREE.BufferGeometry();
+  g.setAttribute('position', new THREE.Float32BufferAttribute(pos, 3));
+  g.setAttribute('aArc', new THREE.Float32BufferAttribute(arc, 1));
+  g.setAttribute('aRnd', new THREE.Float32BufferAttribute(rnd, 1));
+  const m = new THREE.ShaderMaterial({
+    transparent: true,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    uniforms: { uT: { value: 0 }, uDraw: { value: 0 }, uAlpha: { value: 0 }, uColor: { value: new THREE.Color('#2bd9ff') } },
+    vertexShader: /* glsl */ `
+      attribute float aArc;
+      attribute float aRnd;
+      varying float vArc;
+      varying float vRnd;
+      varying float vFacing;
+      void main() {
+        vArc = aArc; vRnd = aRnd;
+        vec4 wp = modelMatrix * vec4(position, 1.0);
+        vFacing = dot(normalize(wp.xyz), normalize(cameraPosition - wp.xyz));
+        gl_Position = projectionMatrix * viewMatrix * wp;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform float uT, uDraw, uAlpha;
+      uniform vec3 uColor;
+      varying float vArc;
+      varying float vRnd;
+      varying float vFacing;
+      void main() {
+        float drawn = uDraw * 3.2 - vArc - vRnd * 0.4;
+        if (drawn < 0.0) discard;
+        float tip = exp(-drawn * 30.0) * 3.0;
+        float p = fract(vArc * 3.0 - uT * 0.9 + vRnd);
+        float pulse = pow(smoothstep(0.85, 1.0, p), 3.0) * 2.5;
+        float back = smoothstep(-0.1, 0.25, vFacing);
+        vec3 c = uColor * (0.28 + pulse) + vec3(1.0) * (tip + pulse * 0.4);
+        gl_FragColor = vec4(c * uAlpha * back, 1.0);
+      }
+    `,
+  });
+  return new THREE.LineSegments(g, m);
+}
+
+// Great-circle arcs that lift off the surface; a bright head travels along.
+export function createArcs(pairs, seed = 5) {
+  const rnd = mulberry32(seed);
+  const pos = [];
+  const u = [];
+  const t0 = [];
+  const SEG = 48;
+  const a = [0, 0, 0];
+  const b = [0, 0, 0];
+  for (const [p, q] of pairs) {
+    const d = angDist(p[0], p[1], q[0], q[1]);
+    if (d < 0.05) continue;
+    const brg = bearing(p[0], p[1], q[0], q[1]);
+    const lift = 0.015 + d * 0.07;
+    const start = rnd();
+    let prev = null;
+    for (let i = 0; i <= SEG; i++) {
+      const f = i / SEG;
+      const [lo, la] = destination(p[0], p[1], brg, d * f);
+      const h = 1.002 + Math.sin(Math.PI * f) * lift;
+      llToVec(lo, la, h, b);
+      if (prev) {
+        pos.push(...prev, ...b);
+        u.push((i - 1) / SEG, f);
+        t0.push(start, start);
+      }
+      prev = [...b];
+    }
+  }
+  const g = new THREE.BufferGeometry();
+  g.setAttribute('position', new THREE.Float32BufferAttribute(pos, 3));
+  g.setAttribute('aU', new THREE.Float32BufferAttribute(u, 1));
+  g.setAttribute('aT0', new THREE.Float32BufferAttribute(t0, 1));
+  const m = new THREE.ShaderMaterial({
+    transparent: true,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    uniforms: { uT: { value: 0 }, uAlpha: { value: 0 }, uColor: { value: new THREE.Color('#5ff6ff') } },
+    vertexShader: /* glsl */ `
+      attribute float aU;
+      attribute float aT0;
+      varying float vU;
+      varying float vT0;
+      void main() {
+        vU = aU; vT0 = aT0;
+        gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0);
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform float uT, uAlpha;
+      uniform vec3 uColor;
+      varying float vU;
+      varying float vT0;
+      void main() {
+        float head = uT * 0.55 - vT0 * 1.6;   // each arc launches at its own time
+        float k = head - vU;
+        if (k < 0.0) discard;
+        float trail = exp(-k * 3.5);
+        float hot = exp(-k * 40.0) * 2.0;
+        vec3 c = uColor * (0.15 + trail) + vec3(1.0) * hot;
+        gl_FragColor = vec4(c * uAlpha, 1.0);
+      }
+    `,
+  });
+  return new THREE.LineSegments(g, m);
+}
+
+// The digital twin's lattice: a geodesic shell that grows outward.
+export function createLattice() {
+  const ico = new THREE.IcosahedronGeometry(1, 4);
+  const edges = new THREE.WireframeGeometry(ico);
+  const p = edges.getAttribute('position');
+  const rnd = [];
+  // build order: a sweep out from the seed (+X, Null Island) with a little jitter,
+  // so the shell visibly constructs itself the way the culture grew
+  for (let i = 0; i < p.count; i += 2) {
+    const mx = (p.getX(i) + p.getX(i + 1)) / 2;
+    const my = (p.getY(i) + p.getY(i + 1)) / 2;
+    const mz = (p.getZ(i) + p.getZ(i + 1)) / 2;
+    const ang = Math.acos(Math.max(-1, Math.min(1, mx / Math.hypot(mx, my, mz)))) / Math.PI;
+    const h = Math.sin(mx * 91.7 + my * 47.3 + mz * 13.1) * 43758.5;
+    const v = Math.min(0.999, ang * 0.9 + (h - Math.floor(h)) * 0.08);
+    rnd.push(v, v);
+  }
+  edges.setAttribute('aRnd', new THREE.Float32BufferAttribute(rnd, 1));
+  const m = new THREE.ShaderMaterial({
+    transparent: true,
+    depthWrite: false,
+    blending: THREE.AdditiveBlending,
+    uniforms: { uAlpha: { value: 0 }, uBuild: { value: 0 }, uT: { value: 0 }, uColor: { value: new THREE.Color('#38e8ff') } },
+    vertexShader: /* glsl */ `
+      attribute float aRnd;
+      varying float vRnd;
+      varying vec3 vP;
+      varying float vFacing;
+      void main() {
+        vRnd = aRnd; vP = normalize(position);
+        vec4 wp = modelMatrix * vec4(position, 1.0);
+        vFacing = dot(normalize(wp.xyz), normalize(cameraPosition - wp.xyz));
+        gl_Position = projectionMatrix * viewMatrix * wp;
+      }
+    `,
+    fragmentShader: /* glsl */ `
+      uniform float uAlpha, uBuild, uT;
+      uniform vec3 uColor;
+      varying float vRnd;
+      varying vec3 vP;
+      varying float vFacing;
+      void main() {
+        if (vRnd > uBuild) discard;
+        float fresh = exp(-(uBuild - vRnd) * 18.0);
+        float shimmer = 0.6 + 0.4 * sin(uT * 3.0 + vRnd * 40.0);
+        // silhouette-weighted: the shell reads as a sphere, not a net over the planet
+        float rim = 1.0 - abs(vFacing);
+        float back = mix(0.18, 1.0, pow(rim, 1.5));
+        vec3 c = uColor * (0.3 * shimmer + fresh * 1.6) + vec3(1.0) * fresh * 0.7;
+        gl_FragColor = vec4(c * uAlpha * back, 1.0);
+      }
+    `,
+  });
+  return new THREE.LineSegments(edges, m);
+}

intro-sequence/src/main.js

@@ -0,0 +1,832 @@
+import * as THREE from 'three';
+import * as satellite from 'satellite.js';
+import { T, FPS, FEEDS, CITIES, DURATION, captureTimes, clamp, lerp, ramp, smooth, win, easeInOut, expoOut, mulberry32 } from './timeline.js';
+import { loadCity, buildCity, loopPath } from './city.js';
+import { llToVec, subsolar, angDist, D2R, R2D, EARTH_KM } from './geo.js';
+import { createGlobe } from './globe.js';
+import { createCoastline, createBorders, createMycelium, createCables, createArcs, createLattice } from './lines.js';
+import { createMovers, createEvents, createSatellites, createOrbitRings, createWind, createStars } from './layers.js';
+import { createPost } from './post.js';
+import { createHUD } from './hud.js';
+
+const qs = new URLSearchParams(location.search);
+const W = +qs.get('w') || 1920;
+const H = +qs.get('h') || 1080;
+const PORTRAIT = H > W;
+const SEED_LL = [0, 0]; // `seed --origin null` — Null Island
+
+const status = (m) => {
+  window.__status = m;
+  console.log('[gev]', m);
+};
+
+async function json(path) {
+  try {
+    const r = await fetch(path);
+    if (!r.ok) throw new Error(r.status);
+    return await r.json();
+  } catch (e) {
+    console.warn('missing', path, e.message);
+    return null;
+  }
+}
+async function text(path) {
+  try {
+    const r = await fetch(path);
+    return r.ok ? await r.text() : null;
+  } catch {
+    return null;
+  }
+}
+function tex(path, { srgb = true, mips = true } = {}) {
+  return new Promise((res) => {
+    new THREE.TextureLoader().load(
+      path,
+      (t) => {
+        if (srgb) t.colorSpace = THREE.SRGBColorSpace;
+        t.anisotropy = 8;
+        t.generateMipmaps = mips;
+        t.minFilter = mips ? THREE.LinearMipmapLinearFilter : THREE.LinearFilter;
+        t.wrapS = THREE.RepeatWrapping;
+        res(t);
+      },
+      undefined,
+      () => {
+        console.warn('missing texture', path);
+        const d = new THREE.DataTexture(new Uint8Array([0, 0, 0, 255]), 1, 1);
+        d.needsUpdate = true;
+        res(d);
+      },
+    );
+  });
+}
+function img(path) {
+  return new Promise((res) => {
+    const im = new Image();
+    im.onload = () => res(im);
+    im.onerror = () => res(null);
+    im.src = path;
+  });
+}
+
+// ------------------------------------------------------------------ boot
+async function init() {
+  status('loading');
+  const canvas = document.getElementById('c');
+  canvas.width = W;
+  canvas.height = H;
+  canvas.style.width = W + 'px';
+  canvas.style.height = H + 'px';
+
+  await document.fonts.ready;
+  await Promise.all([
+    document.fonts.load('400 20px "JetBrains Mono"'),
+    document.fonts.load('500 20px "JetBrains Mono"'),
+    document.fonts.load('200 20px Inter'),
+    document.fonts.load('300 20px Inter'),
+    document.fonts.load('500 20px Inter'),
+  ]);
+
+  const [flights, mil, vessels, quakes, fires, wind, cables, coast, borders, cities, airports, radio, bikes, tleText, tleGroups, heroIdx, camIdx, extra, plants, pads] =
+    await Promise.all([
+      json('data/flights.json'),
+      json('data/military.json'),
+      json('data/vessels.json'),
+      json('data/quakes.json'),
+      json('data/fires.json'),
+      json('data/wind.json'),
+      json('data/cables.json'),
+      json('data/coastline.json'),
+      json('data/borders.json'),
+      json('data/cities.json'),
+      json('data/airports.json'),
+      json('data/radio.json'),
+      json('data/bikes.json'),
+      text('data/tle.txt'),
+      json('data/tle_groups.json'),
+      json('imagery/hero/index.json'),
+      json('cctv/index.json'),
+      json('data/extra_counts.json'),
+      json('data/power_plants.json'),
+      json('data/launch_sites.json'),
+    ]);
+
+  const [dayTex, nightTex, cloudTex] = await Promise.all([
+    tex('imagery/earth_day.jpg'),
+    tex('imagery/earth_night.jpg'),
+    tex('imagery/clouds.jpg', { srgb: false }),
+  ]);
+
+  // Hero captures (Esri synthetic screenshots) and CCTV stills
+  const heroes = [];
+  for (const h of heroIdx || []) {
+    const [wide, close] = await Promise.all([img(`imagery/hero/${h.slug}_wide.jpg`), img(`imagery/hero/${h.slug}_close.jpg`)]);
+    if (wide && close) heroes.push({ ...h, wide, close });
+  }
+  const cams = [];
+  for (const c of camIdx || []) {
+    const im = await img(`cctv/${c.file}`);
+    if (im) cams.push({ ...c, img: im });
+  }
+  status(`assets: ${heroes.length} heroes, ${cams.length} cams`);
+
+  // ---------------------------------------------------------------- scene
+  const renderer = new THREE.WebGLRenderer({ canvas, antialias: false, preserveDrawingBuffer: true, powerPreference: 'high-performance' });
+  renderer.setPixelRatio(1);
+  renderer.setSize(W, H, false);
+  renderer.autoClear = false;
+
+  const scene = new THREE.Scene();
+  const FOV = 26;
+  const camera = new THREE.PerspectiveCamera(FOV, W / H, 0.005, 3000);
+
+  const snapT = new Date((flights?.t || Date.now() / 1000) * 1000);
+  const sunLL = subsolar(snapT);
+  const sunV = new THREE.Vector3(...llToVec(sunLL[0], sunLL[1]));
+
+  const globe = createGlobe({ dayTex, nightTex, cloudTex });
+  globe.uniforms.uSeed.value.set(...llToVec(SEED_LL[0], SEED_LL[1]));
+  globe.uniforms.uSun.value.copy(sunV);
+  globe.uniforms.uWave.value.set(...T.zWave);
+  scene.add(globe.group);
+
+  const stars = createStars();
+  scene.add(stars.group);
+
+  const coastline = coast ? createCoastline(coast.lines, SEED_LL) : null;
+  const borderL = borders ? createBorders(borders.lines, SEED_LL) : null;
+  const myc = createMycelium(SEED_LL);
+  [coastline, borderL, myc].forEach((o) => o && scene.add(o));
+
+  const cableL = cables ? createCables(cables.cables) : null;
+  if (cableL) scene.add(cableL);
+
+  // live feeds
+  const L = {};
+  if (flights) L.air = createMovers(flights.rows, { color: '#e8fbff', trailColor: '#4fd8ff', size: 2.0, altScale: 10, seed: 2 });
+  if (mil) L.mil = createMovers(mil.rows, { color: '#ffbf5a', trailColor: '#ff9a2a', size: 4.0, altScale: 10, revealSpread: 0.6, seed: 4 });
+  if (vessels) L.sea = createMovers(vessels.rows.map((r) => [r[0], r[1], 0, r[3], (r[2] || 0) * 0.5144]), { color: '#52ffc8', trailColor: '#1fd6a0', size: 1.5, gain: 0.45, altScale: 0, seed: 6 });
+  const quakeRowsX = (quakes?.rows || []).filter((r) => r[3] >= 2.5).map((r) => [r[0], r[1], r[3]]);
+  const quakeRows = quakeRowsX;
+  L.quake = createEvents(quakeRows, { color: '#ff3d3d', size: 1.6, mode: 'ring', weightFn: (m) => clamp((m - 2.4) / 4.5, 0.05, 1.3), spread: 1.6 });
+  const fireRows = (fires?.rows || []).map((r) => [r[0], r[1], r[2]]);
+  L.fire = createEvents(fireRows, { color: '#ff6a14', size: 1.15, gain: 0.32, mode: 'flicker', weightFn: (f) => clamp(Math.log10(1 + f) / 2.5, 0, 1.2), spread: 1.4 });
+  if (wind) L.wind = createWind(wind, { count: PORTRAIT ? 6000 : 7000 });
+  Object.values(L).forEach((l) => scene.add(l.group));
+
+  // satellites
+  const sats = [];
+  if (tleText) {
+    const lines = tleText.split(/\r?\n/).map((s) => s.trimEnd()).filter(Boolean);
+    for (let i = 0; i < lines.length - 1; i++) {
+      if (lines[i].startsWith('1 ') && lines[i + 1].startsWith('2 ')) {
+        const name = i > 0 && !lines[i - 1].startsWith('2 ') && !lines[i - 1].startsWith('1 ') ? lines[i - 1].replace(/^0 /, '').trim() : '';
+        try {
+          const rec = satellite.twoline2satrec(lines[i], lines[i + 1]);
+          sats.push({ rec, name, norad: +lines[i].slice(2, 7) || 0 });
+        } catch {}
+        i++;
+      }
+    }
+  }
+  const stationSet = new Set(tleGroups?.groups_norad?.stations || [25544]);
+  const satL = createSatellites(Math.max(1, sats.length));
+  sats.forEach((s, i) => (satL.kind[i] = stationSet.has(s.norad) ? 1 : 0));
+  satL.group.geometry.getAttribute('aK').needsUpdate = true;
+  scene.add(satL.group);
+  const satByNorad = new Map(sats.map((s, i) => [s.norad, i]));
+
+  // orbit rings in an ECI-aligned group, rotated by -GMST each frame
+  const ringGroup = new THREE.Group();
+  scene.add(ringGroup);
+  // LEO rings for the orbital beat; GPS/GEO rings only once the camera is far out
+  const ringIds = [25544, 20580, 48274, 41866, 51850, 40105, 28474, 43226];
+  const ringPaths = [];
+  const highPaths = [];
+  for (const id of ringIds) {
+    const i = satByNorad.get(id);
+    if (i === undefined) continue;
+    const rec = sats[i].rec;
+    const period = (2 * Math.PI) / rec.no; // minutes
+    const path = [];
+    for (let k = 0; k <= 240; k++) {
+      const d = new Date(snapT.getTime() + (k / 240) * period * 60000);
+      const pv = satellite.propagate(rec, d);
+      if (!pv.position) continue;
+      const p = pv.position;
+      path.push([p.x / EARTH_KM, p.z / EARTH_KM, -p.y / EARTH_KM]);
+    }
+    if (path.length > 10) (Math.hypot(...path[0]) < 1.3 ? ringPaths : highPaths).push(path);
+  }
+  const rings = createOrbitRings(ringPaths);
+  const ringsHigh = createOrbitRings(highPaths, '#a9a2ff');
+  ringGroup.add(rings, ringsHigh);
+
+  // data arcs for saturation: between big cities, cameras and cable ends
+  const arcPairs = [];
+  {
+    const r = mulberry32(42);
+    const pool = (cities?.rows || []).slice(0, 400).map((c) => [c[0], c[1]]);
+    for (let i = 0; i < 150 && pool.length > 2; i++) {
+      const a = pool[Math.floor(Math.pow(r(), 1.6) * pool.length)];
+      const b = pool[Math.floor(r() * pool.length)];
+      if (angDist(a[0], a[1], b[0], b[1]) > 0.15) arcPairs.push([a, b]);
+    }
+  }
+  const arcs = createArcs(arcPairs);
+  scene.add(arcs);
+
+  const lattice = createLattice();
+  scene.add(lattice);
+
+  const pxScale = Math.min(W, H) / 1080;
+  for (const l of [...Object.values(L), satL, stars]) if (l.uniforms.uPx) l.uniforms.uPx.value = pxScale;
+
+  // ---------------------------------------------------------------- HUD + post
+  const hudCanvas = document.createElement('canvas');
+  hudCanvas.width = W;
+  hudCanvas.height = H;
+  const post = createPost(renderer, W, H, hudCanvas);
+  const hudCtx = hudCanvas.getContext('2d');
+
+  const counts = {
+    air: flights?.rows.length || 0,
+    mil: mil?.rows.length || 0,
+    sea: vessels?.rows.length || 0,
+    orbit: sats.length,
+    quake: quakes?.rows.length || 0,
+    fire: fires?.rows.length || 0,
+    wind: wind ? wind.nx * wind.ny : 0,
+    cable: cables?.cables.length || 0,
+    cctv: extra?.cctv_catalog || cams.length,
+    cities: cities?.rows.length || 0,
+    cctvCountries: extra?.cctv_countries || new Set(cams.map((c) => c.country)).size,
+    cctvSources: extra?.cctv_sources ? Object.keys(extra.cctv_sources).length : new Set(cams.map((c) => c.source)).size,
+  };
+  const rapidList = [];
+  if (airports) rapidList.push(['AIRPORTS', airports.rows.length]);
+  if (radio) rapidList.push(['RADIO STATIONS', radio.rows.length]);
+  if (bikes) rapidList.push(['BIKESHARE STATIONS', bikes.rows.length]);
+  if (plants) rapidList.push(['POWER PLANTS', plants.rows.length]);
+  if (pads) rapidList.push(['LAUNCH PADS', pads.rows.length]);
+  rapidList.push(['POPULATED PLACES', counts.cities]);
+  rapidList.push(['LAND BORDERS', borders?.lines.length || 0]);
+
+  // notable callouts — real records picked from the feeds
+  const pick = {
+    flights: pickFlights(flights),
+    mil: (mil?.rows || []).filter((r) => r[5] && r[7] && r[2] > 1500 && r[4] > 80).slice(0, 8),
+    ships: (vessels?.rows || []).filter((r) => r[5] && r[2] > 6).slice(0, 40),
+    quakeTop: (quakes?.rows || []).slice().sort((a, b) => b[3] - a[3]).slice(0, 4),
+    fireTop: (fires?.rows || []).slice().sort((a, b) => b[2] - a[2]).slice(0, 3),
+    cities: (cities?.rows || []).slice(0, 220),
+  };
+
+  const capT = captureTimes(heroes.length);
+  // v2 assets: the capture flurry, street cameras, detections
+  const flurryIdx = (await json('imagery/flurry/index.json')) || [];
+  const flurry = [];
+  for (const f of flurryIdx) {
+    const im = await img(`imagery/flurry/${f.file}`);
+    if (im) flurry.push({ ...f, img: im });
+  }
+  const detections = (await json('cctv/detections.json')) || {};
+  const nycIdx = (await json('cctv/nyc/index.json')) || [];
+  const nycCams = [];
+  for (const c of nycIdx) {
+    const im = await img(`cctv/nyc/${c.file}`);
+    if (im) nycCams.push({ ...c, img: im, det: detections[`nyc/${c.file}`] || detections[`cctv/nyc/${c.file}`] || [] });
+  }
+  for (const c of cams) c.det = detections[c.file] || detections[`cctv/${c.file}`] || [];
+  status(`v2 assets: ${flurry.length} flurry, ${nycCams.length} nyc cams, ${Object.keys(detections).length} detection sets`);
+
+  // ---------------------------------------------------------------- cities
+  const cityCam = new THREE.PerspectiveCamera(PORTRAIT ? 60 : 36, W / H, 0.05, 600);
+  const cityScenes = [];
+  for (const c of CITIES) {
+    const d = await loadCity(c.slug);
+    if (!d.meta) {
+      console.warn('city missing', c.slug);
+      continue;
+    }
+    const built = buildCity(d, { modeled: modeledFor(c.slug, d) });
+    cityScenes.push({ ...c, d, built });
+    status(`city ${c.slug}: ${JSON.stringify(built.stats)}`);
+  }
+  window.__cities = cityScenes;
+  const CITY_CAMS = {
+    everest: [[[17, 26, 22], [0, 4.5, 0]], [[7, 16, 17], [0, 6, -1]], [[-9, 12.5, 13], [0, 6.5, 0]]],
+    nyc: [[[0.2, 7.5, 2.2], [0, 0, -0.3]], [[1.7, 2.7, 2.5], [0, 0.1, -0.4]], [[2.7, 1.15, 0.5], [0.1, 0.15, -0.6]]],
+    boston: [[[-0.4, 5.6, 3.4], [0, 0, 0]], [[1.3, 2.5, 2.7], [0, 0, -0.2]], [[2.5, 1.35, 1.0], [0.1, 0.05, -0.3]]],
+    lax: [[[-4.2, 2.8, 3.6], [0, 0, 0]], [[-1.0, 1.5, 3.0], [0.3, 0, 0]], [[1.9, 0.95, 2.3], [0.6, 0, -0.2]]],
+    bragg: [[[0, 9, 8], [0, 0, 0]], [[-3.2, 4.8, 5.2], [0.3, 0, 0]], [[-5.2, 2.8, 2.1], [0.5, 0, 0]]],
+  };
+  const camCurves = {};
+  for (const [k, keys] of Object.entries(CITY_CAMS)) {
+    const s = PORTRAIT ? 1.18 : 1;
+    camCurves[k] = {
+      pos: new THREE.CatmullRomCurve3(keys.map(([p, q]) => new THREE.Vector3(q[0] + (p[0] - q[0]) * s, q[1] + (p[1] - q[1]) * s, q[2] + (p[2] - q[2]) * s))),
+      tgt: new THREE.CatmullRomCurve3(keys.map(([, q]) => new THREE.Vector3(...q))),
+    };
+  }
+  const KMV = 0.001;
+  const cv = new THREE.Vector3();
+  function projectCity(x, y, z = 0) {
+    cv.set(x * KMV, z * KMV, -y * KMV).project(cityCam);
+    return { x: (cv.x * 0.5 + 0.5) * W, y: (-cv.y * 0.5 + 0.5) * H, vis: cv.z < 1 && cv.z > -1 };
+  }
+
+  const hud = createHUD({ W, H, PORTRAIT, heroes, cams, counts, rapidList, pick, capT, snapT, sunLL, flurry, nycCams });
+
+  // ---------------------------------------------------------------- camera director
+  // Keys: [t, lon, lat, g (globe radius / half the short side), shiftX, shiftY, roll]
+  const sx = PORTRAIT ? 0 : 0.26;
+  const sy = PORTRAIT ? 0.2 : 0;
+  const KEYS = [
+    [0, 0, 0, 0.6, 0, 0, 0],
+    [8.7, 0, 0, 0.6, 0, 0, 0],
+    [16.6, -1.5, 1.5, 0.62, 0, 0, 0],
+    [19.5, 4, 6, 0.7, 0, 0, -0.01],
+    [22.6, 14, 12, 0.74, 0, 0, -0.02],
+    // the flurry: the planet whips a full turn, accelerating then braking
+    [23.6, 20, 12, 0.74, 0, 0, -0.02],
+    [25.0, 50, 14, 0.74, 0, 0, -0.03],
+    [26.2, 120, 16, 0.72, 0, 0, -0.04],
+    [27.2, 230, 18, 0.72, 0, 0, -0.04],
+    [28.2, 330, 24, 0.78, 0, 0, -0.03],
+    [29.2, 375, 30, 0.9, sx * 0.3, sy * 0.3, -0.02],
+    [30.0, 384, 36, 0.98, sx * 0.5, sy * 0.5, -0.02],
+    [31.8, 374, 58, 1.85, sx, sy, -0.03],
+    [32.8, 368, 59, 1.9, sx, sy, -0.03],
+    [34.4, 305, 43, 1.0, sx, sy, -0.01],
+    [35.6, 268, 30, 0.5, sx, sy, 0.0],
+    [37.6, 225, 20, 0.62, sx, sy, 0.02],
+    [39.4, 175, 2, 0.7, sx, sy, 0.01],
+    [41.0, 150, 6, 0.78, sx, sy, 0.0],
+    // descent: swing to the Himalaya and fall in
+    [42.4, 100, 22, 1.1, sx * 0.4, sy * 0.4, 0.0],
+    [43.2, 88, 27.5, 3.5, 0, 0, 0.0],
+    [43.7, 87, 28, 9.0, 0, 0, 0.0],
+    // behind the camera wall, and back out for saturation
+    [71.0, 205, 16, 0.9, 0, 0, 0.0],
+    [76.4, 200, 18, 0.9, 0, 0, 0.0],
+    [80.0, 178, 24, 0.5, 0, 0, 0.0],
+    [84.4, 148, 22, 0.16, 0, 0, 0.0],
+  ];
+  // Title framing: the planet becomes the iris of the logo.
+  const eye = hud.eyeLayout;
+
+  // Each flurry capture fires as its real location rotates into view on the
+  // leading (east) side of the disc during the spin (18° east of centre).
+  {
+    const samples = [];
+    for (let i = 0; i <= 600; i++) {
+      const tt = T.flurry + (i / 600) * (T.flurryEnd - T.flurry);
+      samples.push([tt, camAt(tt).lon]);
+    }
+    const lo = samples[0][1];
+    const hi = samples[samples.length - 1][1];
+    for (const f of flurry) {
+      let L = f.lon - 18;
+      while (L < lo) L += 360;
+      if (L > hi) continue;
+      const s = samples.find((q) => q[1] >= L);
+      if (s) f.t = s[0] + (hash01(f.lat * 13.3) - 0.5) * 0.08;
+    }
+  }
+
+  function camAt(t) {
+    if (t >= T.title - 0.05) {
+      const g = eye.irisR / (Math.min(W, H) / 2);
+      const k = t - T.title;
+      return { lon: 108 + k * 1.6, lat: 12, g, shiftX: 0, shiftY: (H / 2 - eye.cy) / (Math.min(W, H) / 2), roll: 0 };
+    }
+    let i = 0;
+    while (i < KEYS.length - 2 && t > KEYS[i + 1][0]) i++;
+    const k0 = KEYS[Math.max(0, i - 1)];
+    const k1 = KEYS[i];
+    const k2 = KEYS[i + 1];
+    const k3 = KEYS[Math.min(KEYS.length - 1, i + 2)];
+    const u = clamp((t - k1[0]) / (k2[0] - k1[0]));
+    const out = [];
+    for (let c = 1; c < 7; c++) {
+      const dt = k2[0] - k1[0];
+      const m1 = ((k2[c] - k0[c]) / Math.max(1e-3, k2[0] - k0[0])) * dt;
+      const m2 = ((k3[c] - k1[c]) / Math.max(1e-3, k3[0] - k1[0])) * dt;
+      const u2 = u * u;
+      const u3 = u2 * u;
+      out[c] = (2 * u3 - 3 * u2 + 1) * k1[c] + (u3 - 2 * u2 + u) * m1 + (-2 * u3 + 3 * u2) * k2[c] + (u3 - u2) * m2;
+    }
+    // breathing drift so the shot never feels locked off
+    const drift = smooth(t, 8, 12);
+    return {
+      lon: out[1] + Math.sin(t * 0.21) * 0.6 * drift,
+      lat: out[2] + Math.sin(t * 0.17 + 1.3) * 0.4 * drift,
+      g: out[3],
+      shiftX: out[4],
+      shiftY: out[5],
+      roll: out[6],
+    };
+  }
+
+  const HITS = [
+    [T.collapse, 0.5],
+    [T.substrate, 0.7],
+    [T.indexed, 0.9],
+    [T.cctvWall, 0.5],
+    [T.cctvOut, 0.6],
+    [T.dishBreak, 1.0],
+    [T.eyeOpen, 0.4],
+  ];
+  function impulse(t, decay = 6) {
+    let v = 0;
+    for (const [h, a] of HITS) if (t >= h) v += a * Math.exp(-(t - h) * decay);
+    return v;
+  }
+
+  function placeCamera(t) {
+    const c = camAt(t);
+    const minDim = Math.min(W, H);
+    const tanHalf = Math.tan((FOV * D2R) / 2);
+    const tanA = (c.g * minDim) / H * tanHalf;
+    const dist = 1 / Math.sin(Math.atan(tanA));
+    const shake = impulse(t, 9) * 0.0025;
+    const sh1 = Math.sin(t * 91.0) * shake;
+    const sh2 = Math.cos(t * 77.0) * shake;
+    camera.position.set(...llToVec(c.lon, c.lat, dist));
+    camera.up.set(0, 1, 0);
+    camera.lookAt(0, 0, 0);
+    camera.rotateZ(c.roll + sh1 * 2);
+    camera.near = Math.max(0.002, dist - 30);
+    camera.far = dist + 2000;
+    // shift the globe on screen without changing perspective
+    const offX = -c.shiftX * (minDim / 2) + sh1 * W;
+    const offY = c.shiftY * (minDim / 2) + sh2 * H;
+    camera.setViewOffset(W, H, offX, offY, W, H);
+    camera.updateProjectionMatrix();
+    camera.updateMatrixWorld();
+    return { ...c, dist };
+  }
+
+  // ---------------------------------------------------------------- per-frame state
+  const tmpV = new THREE.Vector3();
+  function project(lon, lat, r = 1) {
+    tmpV.set(...llToVec(lon, lat, r));
+    const n = tmpV.clone().normalize();
+    const toCam = camera.position.clone().sub(tmpV).normalize();
+    const facing = r <= 1.2 ? n.dot(toCam) : 1;
+    tmpV.project(camera);
+    return { x: (tmpV.x * 0.5 + 0.5) * W, y: (-tmpV.y * 0.5 + 0.5) * H, vis: facing > 0.05 && tmpV.z < 1, facing };
+  }
+  function projectVec(v) {
+    tmpV.set(v[0], v[1], v[2]);
+    tmpV.project(camera);
+    return { x: (tmpV.x * 0.5 + 0.5) * W, y: (-tmpV.y * 0.5 + 0.5) * H, z: tmpV.z };
+  }
+
+  function frontAngle(t) {
+    if (t < T.growStart) return -1;
+    const x = ramp(t, T.growStart, T.growEnd);
+    const k = 3;
+    const base = Math.PI * (Math.exp(k * x) - 1) / (Math.exp(k) - 1);
+    return base + Math.max(0, t - T.growEnd) * 0.6;
+  }
+
+  const satScratch = { idx: -1 };
+  function updateSatellites(t, simDate) {
+    const gmst = satellite.gstime(simDate);
+    ringGroup.rotation.y = -gmst;
+    if (satScratch.t === t) return gmst;
+    satScratch.t = t;
+    const p = satL.positions;
+    for (let i = 0; i < sats.length; i++) {
+      const pv = satellite.propagate(sats[i].rec, simDate);
+      const e = pv && pv.position;
+      if (!e || isNaN(e.x)) {
+        p[i * 3] = p[i * 3 + 1] = p[i * 3 + 2] = 0;
+        continue;
+      }
+      const ecf = satellite.eciToEcf(e, gmst);
+      p[i * 3] = ecf.x / EARTH_KM;
+      p[i * 3 + 1] = ecf.z / EARTH_KM;
+      p[i * 3 + 2] = -ecf.y / EARTH_KM;
+    }
+    satL.attr.needsUpdate = true;
+    return gmst;
+  }
+
+  function feedAlpha(t, start) {
+    // everything stays on through saturation, then clears for the title
+    return smooth(t, start, start + 0.25) * (1 - smooth(t, T.cut - 0.05, T.cut));
+  }
+
+  function renderFrame(frame) {
+    const t = frame / FPS;
+    const cam = placeCamera(t);
+    const cityNow = cityScenes.find((c) => t >= c.t0 && t < c.t1);
+    const G = globe.uniforms;
+    const front = frontAngle(t);
+    const titleOn = t >= T.title - 0.05;
+
+    G.uTime.value = t;
+    G.uFront.value = titleOn ? 10 : front;
+    G.uHolo.value = smooth(t, T.growStart - 0.4, T.growStart + 1.2) * (1 - smooth(t, T.indexed - 1, T.indexed + 1));
+    G.uLights.value = smooth(t, T.growStart, T.growStart + 0.8);
+    G.uImagery.value = titleOn ? 1 : smooth(t, 26.5, 29.5);
+    G.uLit.value = titleOn ? 1 : smooth(t, 22.6, 26.0);
+    G.uGridAmt.value = titleOn ? 0 : 1;
+    G.uDim.value = 1 - 0.35 * win(t, T.cctvWall - 0.2, T.cctvOut + 0.3, 0.3, 0.3);
+    globe.cloudU.uAmt.value = titleOn ? 0.6 : smooth(t, T.wind, T.wind + 1.6) * 0.62;
+    globe.atmoU.uAmt.value = titleOn ? 1 : smooth(t, 21.0, 25.0);
+    globe.group.children[1].visible = globe.cloudU.uAmt.value > 0.0005;
+    globe.group.children[2].visible = globe.atmoU.uAmt.value > 0.0005;
+    globe.group.visible = !(t >= T.cut && t < T.title - 0.05) && t >= T.seed - 0.1;
+
+    stars.uniforms.uAlpha.value = titleOn ? 0.5 : smooth(t, T.substrate - 0.5, T.substrate + 2.5) * 0.85 * (t < T.cut ? 1 : 0);
+
+    const vecFade = 1 - smooth(t, T.indexStart + 1.5, T.indexed - 2);
+    if (coastline) {
+      coastline.material.uniforms.uFront.value = front;
+      coastline.material.uniforms.uAlpha.value = 0.95 * vecFade;
+      coastline.visible = vecFade > 0.001 && !titleOn;
+    }
+    if (borderL) {
+      borderL.material.uniforms.uFront.value = front - 0.25;
+      borderL.material.uniforms.uAlpha.value = 0.7 * vecFade;
+      borderL.visible = vecFade > 0.001 && !titleOn;
+    }
+    myc.material.uniforms.uFront.value = front;
+    myc.material.uniforms.uAlpha.value = 0.85 * (1 - smooth(t, T.substrate, T.indexStart + 3));
+    myc.visible = t > T.growStart && t < T.indexStart + 3.2;
+
+    // feeds
+    const dens = clamp((cam.g - 0.12) / 0.75, 0.22, 1);
+    const reveal = (start, dur = 1.6, spread = 1.4) => ((t - start) * (1 + spread)) / dur;
+    const setMover = (l, start, accel) => {
+      if (!l) return;
+      l.uniforms.uSim.value = Math.max(0, t - start) * accel;
+      l.uniforms.uReveal.value = reveal(start, 1.6, l.uniforms.uSpread.value);
+      l.uniforms.uAlpha.value = feedAlpha(t, start) * dens;
+      l.group.visible = t >= start && t < T.cut;
+    };
+    setMover(L.air, T.air, 140);
+    setMover(L.mil, T.mil, 140);
+    setMover(L.sea, T.sea, 1800);
+    const setEv = (l, start, dur = 1.8) => {
+      if (!l) return;
+      l.uniforms.uT.value = t;
+      l.uniforms.uReveal.value = reveal(start, dur, l.uniforms.uSpread.value);
+      l.uniforms.uAlpha.value = feedAlpha(t, start) * dens;
+      l.group.visible = t >= start && t < T.cut;
+    };
+    setEv(L.quake, T.quake, 1.6);
+    setEv(L.fire, T.fire, 1.5);
+    if (L.fire) L.fire.uniforms.uAlpha.value *= dens;
+    if (L.wind) {
+      const on = t >= T.wind && t < T.cut;
+      L.wind.group.visible = on;
+      if (on) {
+        L.wind.update(t - T.wind);
+        L.wind.uniforms.uAlpha.value = feedAlpha(t, T.wind) * 2.2 * dens;
+      }
+    }
+    if (cableL) {
+      const u = cableL.material.uniforms;
+      u.uT.value = t;
+      u.uDraw.value = ramp(t, T.cable, T.cable + 1.8);
+      u.uAlpha.value = feedAlpha(t, T.cable) * 0.9;
+      cableL.visible = t >= T.cable && t < T.cut;
+    }
+
+    // satellites + rings
+    const satOn = t >= T.orbit && t < T.cut;
+    const simDate = new Date(snapT.getTime() + Math.max(0, t - T.orbit) * 45 * 1000);
+    satL.group.visible = satOn;
+    rings.visible = satOn;
+    let gmst = satellite.gstime(simDate);
+    if (satOn) {
+      gmst = updateSatellites(t, simDate);
+      satL.uniforms.uReveal.value = reveal(T.orbit, 1.8, 1.3);
+      satL.uniforms.uAlpha.value = feedAlpha(t, T.orbit) * Math.max(0.45, dens);
+      rings.material.uniforms.uDraw.value = easeInOut(ramp(t, T.orbit + 0.3, T.orbit + 2.4));
+      rings.material.uniforms.uAlpha.value = feedAlpha(t, T.orbit) * 0.8;
+    }
+    ringsHigh.visible = t >= T.saturate + 1 && t < T.cut;
+    ringsHigh.material.uniforms.uDraw.value = easeInOut(ramp(t, T.saturate + 1, T.saturate + 3.5));
+    ringsHigh.material.uniforms.uAlpha.value = feedAlpha(t, T.saturate + 1) * 0.7;
+
+    // saturation: arcs + lattice
+    arcs.visible = t >= T.arcs && t < T.cut;
+    arcs.material.uniforms.uT.value = t - T.arcs;
+    arcs.material.uniforms.uAlpha.value = feedAlpha(t, T.arcs) * 0.9;
+    const twinOn = t >= T.twin && t < T.cut;
+    lattice.visible = twinOn;
+    if (twinOn) {
+      lattice.scale.setScalar(latticeScale(t, cam.dist));
+      lattice.rotation.y = t * 0.05;
+      const lu = lattice.material.uniforms;
+      lu.uBuild.value = ramp(t, T.twin, T.twin + 2.6);
+      lu.uT.value = t;
+      lu.uAlpha.value = smooth(t, T.twin, T.twin + 0.6) * (1 - smooth(t, T.cut - 0.4, T.cut)) * 0.7;
+    }
+
+    // ---- HUD
+    const S = {
+      t,
+      frame,
+      cam,
+      front,
+      gmst,
+      simDate,
+      project,
+      projectVec,
+      satPos: (norad) => {
+        const i = satByNorad.get(norad);
+        if (i === undefined) return null;
+        const p = satL.positions;
+        return [p[i * 3], p[i * 3 + 1], p[i * 3 + 2]];
+      },
+      limbR: limbRadiusPx(cam.dist),
+      center: project(...[cam.lon, cam.lat], 0), // screen position of the globe centre
+      flightPos: (row, accel) => {
+        const sim = Math.max(0, t - T.air) * accel;
+        return advance(row, sim);
+      },
+      shipPos: (row) => advance([row[0], row[1], 0, row[3], (row[2] || 0) * 0.5144], Math.max(0, t - T.sea) * 1800),
+    };
+    S.center = projectVec([0, 0, 0]);
+    S.ctx = hudCtx;
+    S.camPos = camera.position;
+    S.latticeR = latticePx(t, cam.dist);
+    S.ringR = ringR0;
+    let renderScene = scene;
+    let renderCam = camera;
+    if (cityNow) {
+      const lt = t - cityNow.t0;
+      const k = (t - cityNow.t0) / (cityNow.t1 - cityNow.t0);
+      const u = 1 - Math.pow(1 - k, 2.2);
+      const cc = camCurves[cityNow.slug];
+      cityCam.position.copy(cc.pos.getPoint(u));
+      const tg = cc.tgt.getPoint(u);
+      // a hair of handheld drift
+      cityCam.position.x += Math.sin(t * 0.7) * 0.01;
+      cityCam.position.y += Math.sin(t * 0.53) * 0.008;
+      cityCam.lookAt(tg);
+      const sh = impulse(t, 9) * 0.003;
+      cityCam.rotateZ(Math.sin(t * 91) * sh);
+      cityCam.updateMatrixWorld();
+      cityNow.built.update(lt, k, pxScale);
+      // Boston is the transit showcase: let the GTFS lines lead
+      if (cityNow.slug === 'boston' && cityNow.built.roads) cityNow.built.roads.mesh.material.uniforms.uAlpha.value = 0.45;
+      renderScene = cityNow.built.scene;
+      renderCam = cityCam;
+      S.city = { ...cityNow, lt, k, project: projectCity, built: cityNow.built };
+      S.cam = { ...S.cam, lat: cityNow.lat, lon: cityNow.lon, dist: 1 + cityCam.position.y / 6371 };
+    }
+    hud.draw(S);
+
+    // ---- post
+    const glitch =
+      win(t, T.collapse - 0.05, T.collapse + 0.35, 0.02, 0.2) * 0.8 +
+      win(t, T.substrate - 0.02, T.substrate + 0.25, 0.02, 0.2) * 0.5 +
+      win(t, T.indexed - 0.02, T.indexed + 0.3, 0.02, 0.25) * 0.7 +
+      win(t, T.cctvWall - 0.02, T.cctvWall + 0.2, 0.02, 0.15) * 0.5 +
+      win(t, T.cctvOut - 0.05, T.cctvOut + 0.3, 0.02, 0.25) * 0.8 +
+      win(t, T.dishBreak - 0.02, T.dishBreak + 0.4, 0.02, 0.3) * 1.0 +
+      win(t, T.cut - 0.25, T.cut, 0.1, 0.01) * 1.0 +
+      win(t, T.eyeOpen - 0.02, T.eyeOpen + 0.2, 0.02, 0.15) * 0.4 +
+      win(t, T.terrain - 0.35, T.terrain + 0.25, 0.25, 0.2) * 1.0 +
+      CITIES.slice(1).reduce((s, c) => s + win(t, c.t0 - 0.06, c.t0 + 0.22, 0.04, 0.16) * 0.8, 0);
+    const flash =
+      Math.exp(-Math.max(0, t - T.substrate) * 12) * 0.035 * (t >= T.substrate ? 1 : 0) +
+      Math.exp(-Math.max(0, t - T.indexed) * 12) * 0.05 * (t >= T.indexed ? 1 : 0) +
+      Math.exp(-Math.max(0, t - T.dishBreak) * 10) * 0.06 * (t >= T.dishBreak ? 1 : 0) +
+      Math.exp(-Math.max(0, t - T.eyeOpen) * 10) * 0.05 * (t >= T.eyeOpen ? 1 : 0);
+    let fade = smooth(t, 0, 0.6);
+    if (t >= T.cut && t < T.title) fade = 0;
+    fade *= 1 - smooth(t, T.fadeOut, DURATION_END);
+    post.render(renderScene, renderCam, {
+      time: t,
+      frame,
+      bloom: t < T.seed ? 0.7 : lerp(0.85, 1.15, smooth(t, T.saturate, T.cut)),
+      bloomThresh: 0.78,
+      exposure: 1.0,
+      aberr: titleOn ? 0.00025 + glitch * 0.004 : 0.0012 + 0.002 * smooth(t, T.saturate, T.cut) + glitch * 0.004,
+      grain: 0.05,
+      vignette: 0.6,
+      glitch,
+      scan: t < T.seed ? 0.7 : 0.12,
+      flash,
+      fade,
+      hudGain: 1.0,
+    });
+  }
+
+  const RING_R = Math.min(W, H) * (PORTRAIT ? 0.43 : 0.4);
+  function latticePx(t, dist) {
+    const limb = limbRadiusPx(dist) * 1.12;
+    if (t < T.dishBreak) return lerp(limb, RING_R, Math.pow(easeInOut(ramp(t, T.twin, T.dishBreak)), 1.2));
+    return RING_R * (1 + 1.6 * Math.pow(ramp(t, T.dishBreak, T.cut), 0.8));
+  }
+  function latticeScale(t, dist) {
+    const px = latticePx(t, dist);
+    const tanA = (px / (H / 2)) * Math.tan((FOV * D2R) / 2);
+    return dist * Math.sin(Math.atan(tanA));
+  }
+  function limbRadiusPx(dist) {
+    const tanA = Math.tan(Math.asin(1 / dist));
+    return (tanA / Math.tan((FOV * D2R) / 2)) * (H / 2);
+  }
+
+  function advance(row, sim) {
+    // row: [lon, lat, alt, track, vel(m/s)] -> [lon, lat] after sim seconds
+    const d = ((row[4] || 0) / (EARTH_KM * 1000)) * sim;
+    const b = (row[3] || 0) * D2R;
+    const la = row[1] * D2R;
+    const lo = row[0] * D2R;
+    const lat2 = Math.asin(Math.sin(la) * Math.cos(d) + Math.cos(la) * Math.sin(d) * Math.cos(b));
+    const lon2 = lo + Math.atan2(Math.sin(b) * Math.sin(d) * Math.cos(la), Math.cos(d) - Math.sin(la) * Math.sin(lat2));
+    return [lon2 * R2D, lat2 * R2D, row[2] || 0];
+  }
+
+  // the dish's second coming is sized so the twin breaches it exactly on cue
+  const ringR0 = RING_R;
+
+  window.GEV = { renderFrame, ready: true, W, H, frames: Math.round(DURATION_END * FPS), counts, heroes: heroes.length, cams: cams.length, capT };
+  status('ready');
+  if (qs.has('play')) startPlayback(renderFrame);
+}
+
+const DURATION_END = DURATION;
+const hash01 = (n) => {
+  const s = Math.sin(n * 127.1 + 311.7) * 43758.5453;
+  return s - Math.floor(s);
+};
+
+// Modelled actors (always labelled MODELED in the HUD) where real feeds are thin.
+function modeledFor(slug, d) {
+  const out = [];
+  if (slug === 'nyc') {
+    const realHelis = (d.air?.a || []).filter((p) => p[8] === 'A7').length;
+    if (realHelis < 3) {
+      // Hudson and East River corridors, and a hover orbit over Midtown
+      out.push({ name: 'HUDSON CORRIDOR', path: [[-1750, -3300, 300], [-1950, -1000, 330], [-1800, 1500, 350], [-1450, 3300, 320], [-1250, 1500, 300], [-1400, -1000, 290]], speed: 0.09, phase: 0.1, color: '#7dffd6' });
+      out.push({ name: 'EAST RIVER', path: [[1650, -3200, 260], [1900, -800, 280], [2150, 1800, 300], [1750, 2600, 300], [1450, 800, 270], [1350, -1500, 250]], speed: 0.08, phase: 0.55, color: '#7dffd6' });
+      out.push({ name: 'MIDTOWN ORBIT', path: loopPath(-150, 900, 420, 380, 450, 0.3, 40), speed: 0.16, phase: 0.2, color: '#7dffd6' });
+    }
+  }
+  if (slug === 'bragg') {
+    const rw = d.military?.runways?.[0];
+    let cx = 0, cy = 0, rot = 0;
+    if (rw) {
+      const x1 = rw[2], y1 = rw[3], x2 = rw[rw.length - 2], y2 = rw[rw.length - 1];
+      cx = (x1 + x2) / 2;
+      cy = (y1 + y2) / 2;
+      rot = Math.atan2(y2 - y1, x2 - x1);
+    }
+    out.push({ name: 'PATTERN', path: loopPath(cx, cy, 2600, 1100, 330, rot, 48), speed: 0.07, phase: 0.0, color: '#ffb547' });
+    out.push({ name: 'PATTERN', path: loopPath(cx, cy, 2600, 1100, 330, rot, 48), speed: 0.07, phase: 0.5, color: '#ffb547' });
+    out.push({ name: 'ROTARY', path: loopPath(cx - 3000, cy + 2500, 900, 700, 180, 0.4, 32), speed: 0.11, phase: 0.3, color: '#ffb547' });
+  }
+  return out;
+}
+
+// Real-time mode (?play): the same deterministic frames, driven by the audio
+// clock, for use as a live loading sequence on a GPU. Browsers block audio
+// until a gesture, so the first click starts it.
+function startPlayback(renderFrame) {
+  const audio = new Audio('audio/score.wav');
+  const cv = document.getElementById('c');
+  cv.style.cssText = 'width:100vw;height:100vh;object-fit:contain;display:block';
+  const gate = document.createElement('div');
+  gate.textContent = 'CLICK TO INITIALISE';
+  gate.style.cssText = 'position:fixed;inset:0;display:flex;align-items:center;justify-content:center;color:#00f6ff;font:500 14px "JetBrains Mono";letter-spacing:6px;cursor:pointer;background:#000';
+  document.body.appendChild(gate);
+  gate.addEventListener('click', () => {
+    gate.remove();
+    audio.play().catch(() => {});
+    const t0 = performance.now();
+    const tick = () => {
+      const t = audio.currentTime > 0 ? audio.currentTime : (performance.now() - t0) / 1000;
+      if (t < DURATION_END) {
+        renderFrame(Math.min(DURATION_END * FPS - 1, Math.floor(t * FPS)));
+        requestAnimationFrame(tick);
+      }
+    };
+    requestAnimationFrame(tick);
+  });
+}
+
+function pickFlights(f) {
+  if (!f) return [];
+  // long-haul, high, fast, with recognisable callsigns
+  return f.rows
+    .filter((r) => r[5] && r[2] > 9000 && r[4] > 220 && /^[A-Z]{3}\d/.test(r[5]))
+    .sort((a, b) => b[4] - a[4])
+    .slice(0, 120);
+}
+
+init().catch((e) => {
+  status('error: ' + e.message);
+  console.error(e);
+});

intro-sequence/src/post.js

@@ -0,0 +1,218 @@
+import * as THREE from 'three';
+
+// HDR scene -> HUD composited in -> dual-filter bloom -> lens + film finish.
+const QUAD_VS = /* glsl */ `
+  varying vec2 vUv;
+  void main() { vUv = uv; gl_Position = vec4(position.xy, 0.0, 1.0); }
+`;
+
+export function createPost(renderer, W, H, hudCanvas) {
+  const rtOpts = { type: THREE.HalfFloatType, format: THREE.RGBAFormat, depthBuffer: false };
+  const scene = new THREE.WebGLRenderTarget(W, H, { type: THREE.HalfFloatType, samples: 4 });
+  const merged = new THREE.WebGLRenderTarget(W, H, rtOpts);
+  const levels = [];
+  let w = W;
+  let h = H;
+  for (let i = 0; i < 6; i++) {
+    w = Math.max(2, Math.floor(w / 2));
+    h = Math.max(2, Math.floor(h / 2));
+    levels.push({ down: new THREE.WebGLRenderTarget(w, h, rtOpts), up: new THREE.WebGLRenderTarget(w, h, rtOpts) });
+  }
+
+  const hudTex = new THREE.CanvasTexture(hudCanvas);
+  hudTex.colorSpace = THREE.SRGBColorSpace;
+  hudTex.minFilter = THREE.LinearFilter;
+  hudTex.generateMipmaps = false;
+
+  const quad = new THREE.Mesh(new THREE.PlaneGeometry(2, 2));
+  const qScene = new THREE.Scene();
+  qScene.add(quad);
+  const qCam = new THREE.OrthographicCamera(-1, 1, 1, -1, 0, 1);
+
+  const mergeMat = new THREE.ShaderMaterial({
+    uniforms: { tScene: { value: null }, tHud: { value: hudTex }, uHudGain: { value: 1.25 } },
+    vertexShader: QUAD_VS,
+    fragmentShader: /* glsl */ `
+      uniform sampler2D tScene, tHud;
+      uniform float uHudGain;
+      varying vec2 vUv;
+      void main() {
+        vec3 s = texture2D(tScene, vUv).rgb;
+        vec4 hud = texture2D(tHud, vUv);
+        // canvas uploads un-premultiplied: straight-alpha over-composite
+        vec3 c = s * (1.0 - hud.a) + hud.rgb * hud.a * uHudGain;
+        gl_FragColor = vec4(c, 1.0);
+      }
+    `,
+    depthTest: false,
+  });
+
+  const downMat = new THREE.ShaderMaterial({
+    uniforms: { tSrc: { value: null }, uTexel: { value: new THREE.Vector2() }, uThresh: { value: 0 }, uFirst: { value: 0 } },
+    vertexShader: QUAD_VS,
+    fragmentShader: /* glsl */ `
+      uniform sampler2D tSrc;
+      uniform vec2 uTexel;
+      uniform float uThresh, uFirst;
+      varying vec2 vUv;
+      vec3 pre(vec3 c) {
+        if (uFirst < 0.5) return c;
+        float l = max(c.r, max(c.g, c.b));
+        float k = max(l - uThresh, 0.0) / max(l, 1e-4);
+        return min(c * k, vec3(40.0));
+      }
+      void main() {
+        vec2 o = uTexel;
+        vec3 c = pre(texture2D(tSrc, vUv).rgb) * 4.0;
+        c += pre(texture2D(tSrc, vUv + vec2(-o.x, -o.y)).rgb);
+        c += pre(texture2D(tSrc, vUv + vec2( o.x, -o.y)).rgb);
+        c += pre(texture2D(tSrc, vUv + vec2(-o.x,  o.y)).rgb);
+        c += pre(texture2D(tSrc, vUv + vec2( o.x,  o.y)).rgb);
+        gl_FragColor = vec4(c / 8.0, 1.0);
+      }
+    `,
+    depthTest: false,
+  });
+
+  const upMat = new THREE.ShaderMaterial({
+    uniforms: { tSrc: { value: null }, tBase: { value: null }, uTexel: { value: new THREE.Vector2() } },
+    vertexShader: QUAD_VS,
+    fragmentShader: /* glsl */ `
+      uniform sampler2D tSrc, tBase;
+      uniform vec2 uTexel;
+      varying vec2 vUv;
+      void main() {
+        vec2 o = uTexel;
+        vec3 c = texture2D(tSrc, vUv + vec2(-o.x * 2.0, 0.0)).rgb;
+        c += texture2D(tSrc, vUv + vec2(-o.x, o.y)).rgb * 2.0;
+        c += texture2D(tSrc, vUv + vec2(0.0, o.y * 2.0)).rgb;
+        c += texture2D(tSrc, vUv + vec2(o.x, o.y)).rgb * 2.0;
+        c += texture2D(tSrc, vUv + vec2(o.x * 2.0, 0.0)).rgb;
+        c += texture2D(tSrc, vUv + vec2(o.x, -o.y)).rgb * 2.0;
+        c += texture2D(tSrc, vUv + vec2(0.0, -o.y * 2.0)).rgb;
+        c += texture2D(tSrc, vUv + vec2(-o.x, -o.y)).rgb * 2.0;
+        gl_FragColor = vec4(c / 12.0 + texture2D(tBase, vUv).rgb, 1.0);
+      }
+    `,
+    depthTest: false,
+  });
+
+  const finalMat = new THREE.ShaderMaterial({
+    uniforms: {
+      tSrc: { value: null },
+      tBloom: { value: null },
+      uBloom: { value: 0.9 },
+      uExposure: { value: 1 },
+      uTime: { value: 0 },
+      uFrame: { value: 0 },
+      uAberr: { value: 0.0015 },
+      uGrain: { value: 0.045 },
+      uVignette: { value: 0.55 },
+      uGlitch: { value: 0 },
+      uScan: { value: 0 },
+      uFlash: { value: 0 },
+      uFade: { value: 1 },
+      uRes: { value: new THREE.Vector2(W, H) },
+    },
+    vertexShader: QUAD_VS,
+    fragmentShader: /* glsl */ `
+      uniform sampler2D tSrc, tBloom;
+      uniform float uBloom, uExposure, uTime, uFrame, uAberr, uGrain, uVignette, uGlitch, uScan, uFlash, uFade;
+      uniform vec2 uRes;
+      varying vec2 vUv;
+      float h21(vec2 p) { p = fract(p * vec2(123.34, 456.21)); p += dot(p, p + 45.32); return fract(p.x * p.y); }
+      vec3 aces(vec3 x) {
+        const float a = 2.51, b = 0.03, c = 2.43, d = 0.59, e = 0.14;
+        return clamp((x * (a * x + b)) / (x * (c * x + d) + e), 0.0, 1.0);
+      }
+      void main() {
+        vec2 uv = vUv;
+        // block glitch: horizontal slices displaced on transitions
+        if (uGlitch > 0.0) {
+          float row = floor(uv.y * 48.0);
+          float blk = floor(uv.x * 6.0);
+          float r = h21(vec2(row, floor(uFrame * 0.5)));
+          float r2 = h21(vec2(blk, row + floor(uFrame)));
+          if (r < uGlitch * 0.55) uv.x += (r2 - 0.5) * 0.08 * uGlitch;
+          if (r2 < uGlitch * 0.12) uv.y += (r - 0.5) * 0.02;
+        }
+        vec2 d = uv - 0.5;
+        float rr = dot(d, d);
+        vec2 ab = d * rr * uAberr * 7.0 + vec2(uGlitch * 0.006, 0.0);
+        vec3 col;
+        col.r = texture2D(tSrc, uv + ab).r;
+        col.g = texture2D(tSrc, uv).g;
+        col.b = texture2D(tSrc, uv - ab).b;
+        vec3 bl;
+        bl.r = texture2D(tBloom, uv + ab * 1.5).r;
+        bl.g = texture2D(tBloom, uv).g;
+        bl.b = texture2D(tBloom, uv - ab * 1.5).b;
+        col += bl * uBloom;
+        // flashes punch exposure instead of adding a veil, so blacks stay black
+        col *= uExposure * (1.0 + uFlash * 6.0);
+        col = aces(col);
+        // vignette
+        float vig = smoothstep(0.95, 0.18, length(d * vec2(uRes.x / uRes.y, 1.0) * 0.82));
+        col *= mix(1.0, vig, uVignette);
+        // scanlines (boot / CRT moments)
+        col *= 1.0 - uScan * 0.22 * (0.5 + 0.5 * sin(gl_FragCoord.y * 3.14159 * 0.5));
+        col = pow(col, vec3(1.0 / 2.2));
+        // grain after encoding so it lives in the shadows too
+        float g = h21(gl_FragCoord.xy + fract(uFrame * 0.6180339) * 913.0) - 0.5;
+        col += g * uGrain * (1.0 - 0.6 * dot(col, vec3(0.33)));
+        col *= uFade;
+        gl_FragColor = vec4(col, 1.0);
+      }
+    `,
+    depthTest: false,
+  });
+
+  function pass(mat, target) {
+    quad.material = mat;
+    renderer.setRenderTarget(target);
+    renderer.render(qScene, qCam);
+  }
+
+  function render(sceneObj, camera, params) {
+    renderer.setRenderTarget(scene);
+    renderer.setClearColor(0x000000, 1);
+    renderer.clear();
+    renderer.render(sceneObj, camera);
+
+    hudTex.needsUpdate = true;
+    mergeMat.uniforms.tScene.value = scene.texture;
+    mergeMat.uniforms.uHudGain.value = params.hudGain ?? 1.2;
+    pass(mergeMat, merged);
+
+    let src = merged;
+    for (let i = 0; i < levels.length; i++) {
+      downMat.uniforms.tSrc.value = src.texture;
+      downMat.uniforms.uTexel.value.set(0.5 / src.width, 0.5 / src.height);
+      downMat.uniforms.uFirst.value = i === 0 ? 1 : 0;
+      downMat.uniforms.uThresh.value = params.bloomThresh ?? 0.55;
+      pass(downMat, levels[i].down);
+      src = levels[i].down;
+    }
+    let up = levels[levels.length - 1].down;
+    for (let i = levels.length - 2; i >= 0; i--) {
+      upMat.uniforms.tSrc.value = up.texture;
+      upMat.uniforms.tBase.value = levels[i].down.texture;
+      upMat.uniforms.uTexel.value.set(0.5 / up.width, 0.5 / up.height);
+      pass(upMat, levels[i].up);
+      up = levels[i].up;
+    }
+
+    const u = finalMat.uniforms;
+    u.tSrc.value = merged.texture;
+    u.tBloom.value = up.texture;
+    for (const k of ['bloom', 'exposure', 'aberr', 'grain', 'vignette', 'glitch', 'scan', 'flash', 'fade']) {
+      const key = 'u' + k[0].toUpperCase() + k.slice(1);
+      if (params[k] !== undefined) u[key].value = params[k];
+    }
+    u.uTime.value = params.time;
+    u.uFrame.value = params.frame;
+    pass(finalMat, null);
+  }
+
+  return { render };
+}

intro-sequence/src/timeline.js

@@ -0,0 +1,154 @@
+// The film's clock. Everything visual and audible keys off these numbers, so the
+// renderer and the score (audio/score.py reads cues.json, exported from here)
+// stay frame-locked. Pure module: no DOM, safe to import from Node.
+
+export const FPS = 30;
+export const DURATION = 95;
+export const FRAMES = FPS * DURATION;
+
+export const T = {
+  // ACT 0 — the void
+  cursor: 0.9,
+  boot: 1.4,
+  collapse: 4.9,
+  seed: 5.35,
+  beat1: 6.1,
+  beat2: 7.35,
+  dishDraw: 6.3,
+  dishDone: 8.3,
+  aperture: 7.35,
+
+  // ACT 1 — the eye opens; the culture grows and turns out to be drawing the planet
+  growStart: 8.7,
+  coastReached: 13.4,
+  growEnd: 15.6,
+  substrate: 16.0,
+
+  // ACT 2 — indexing the surface, accelerating until it is whipping round the world
+  indexStart: 17.0,
+  zWave: [17.0, 18.5, 19.8], // z3, z4, z5 quadtree waves
+  capStart: 18.0,
+  capRapid: 22.6,
+  flurry: 23.6,
+  flurryEnd: 29.4,
+  capFull: 999, // v1's full-frame extraction now lives in the city act
+  indexed: 30.0,
+
+  // ACT 3 — global ingestion
+  air: 30.6,
+  sea: 32.0,
+  mil: 33.4,
+  orbit: 34.6,
+  quake: 36.6,
+  fire: 38.0,
+  wind: 39.4,
+  cable: 41.0,
+  descend: 42.6,
+
+  // ACT 4 — down into the world
+  terrain: 43.6,
+  nyc: 49.0,
+  boston: 57.0,
+  lax: 61.8,
+  bragg: 66.4,
+  cctv: 71.4,
+  cctvWall: 71.4,
+  rapid: 72.8,
+  cctvOut: 76.4,
+
+  // ACT 5 — saturation; the twin outgrows the dish
+  saturate: 76.6,
+  arcs: 77.3,
+  twin: 79.1,
+  dishBreak: 82.3,
+  omni: 82.9,
+  cut: 84.4,
+
+  // ACT 6 — resolve
+  title: 85.1,
+  eyeOpen: 85.9,
+  wordmark: 87.2,
+  tagline: 88.9,
+  online: 999,
+  fadeOut: 93.0,
+};
+
+// Feeds as they register in the stack (ACT 3). `key` matches a layer.
+export const FEEDS = [
+  { key: 'air', t: T.air, code: 'ADS-B', label: 'AIRCRAFT', src: 'OPENSKY NETWORK' },
+  { key: 'sea', t: T.sea, code: 'AIS', label: 'VESSELS', src: 'KYSTVERKET · DIGITRAFFIC' },
+  { key: 'mil', t: T.mil, code: 'ADS-B', label: 'MILITARY', src: 'ADSB.LOL · ADSB.FI' },
+  { key: 'orbit', t: T.orbit, code: 'TLE', label: 'SATELLITES', src: 'CELESTRAK' },
+  { key: 'quake', t: T.quake, code: 'SEIS', label: 'EARTHQUAKES', src: 'USGS' },
+  { key: 'fire', t: T.fire, code: 'IR', label: 'ACTIVE FIRES', src: 'NASA FIRMS' },
+  { key: 'wind', t: T.wind, code: 'NWP', label: 'WIND · CLOUD', src: 'NOAA GFS · GIBS' },
+  { key: 'cable', t: T.cable, code: 'GEO', label: 'SUBSEA CABLES', src: 'TELEGEOGRAPHY' },
+];
+
+// ACT 4 — the cities, in order
+export const CITIES = [
+  { slug: 'everest', t0: T.terrain, t1: T.nyc, name: 'MOUNT EVEREST', sub: 'KHUMBU · NEPAL / TIBET', lat: 27.9881, lon: 86.925 },
+  { slug: 'nyc', t0: T.nyc, t1: T.boston, name: 'NEW YORK', sub: 'MIDTOWN · MANHATTAN', lat: 40.74, lon: -73.99 },
+  { slug: 'boston', t0: T.boston, t1: T.lax, name: 'BOSTON', sub: 'MBTA · GTFS REALTIME', lat: 42.3555, lon: -71.0605 },
+  { slug: 'lax', t0: T.lax, t1: T.bragg, name: 'LOS ANGELES INTL', sub: 'KLAX · AIRSIDE', lat: 33.9425, lon: -118.4081 },
+  { slug: 'bragg', t0: T.bragg, t1: T.cctv, name: 'FORT BRAGG', sub: 'NORTH CAROLINA · POPE FIELD', lat: 35.158, lon: -79.009 },
+];
+
+// Synthetic captures in ACT 2: the first few take the slow "enhance" path, the
+// rest fire rapidly into the contact sheet, then one blows up full frame.
+export const CAPTURE_SLOW = 3;
+export function captureTimes(count) {
+  const out = [];
+  const slot = [T.capStart, T.capStart + 1.6, T.capStart + 3.1];
+  for (let i = 0; i < Math.min(CAPTURE_SLOW, count); i++) out.push(slot[i]);
+  const rapidN = count - CAPTURE_SLOW;
+  // Accelerating rapid-fire: intervals shrink from ~0.32 s to ~0.11 s.
+  let t = T.capRapid;
+  for (let i = 0; i < rapidN; i++) {
+    out.push(t);
+    const k = i / Math.max(1, rapidN - 1);
+    t += 0.12 - 0.08 * k;
+  }
+  return out;
+}
+
+// ------------------------------------------------------------------ helpers
+export const clamp = (x, a = 0, b = 1) => Math.min(b, Math.max(a, x));
+export const lerp = (a, b, t) => a + (b - a) * t;
+export const ramp = (t, a, b) => clamp((t - a) / (b - a));
+export const smooth = (t, a, b) => {
+  const x = ramp(t, a, b);
+  return x * x * (3 - 2 * x);
+};
+export const easeInOut = (x) => (x < 0.5 ? 4 * x * x * x : 1 - Math.pow(-2 * x + 2, 3) / 2);
+export const easeOut = (x) => 1 - Math.pow(1 - x, 3);
+export const easeIn = (x) => x * x * x;
+export const expoOut = (x) => (x >= 1 ? 1 : 1 - Math.pow(2, -10 * x));
+export const expoInOut = (x) =>
+  x <= 0 ? 0 : x >= 1 ? 1 : x < 0.5 ? Math.pow(2, 20 * x - 10) / 2 : (2 - Math.pow(2, -20 * x + 10)) / 2;
+
+// Window: 0 before a, ramps up over `inDur`, holds, ramps down to 0 ending at b.
+export function win(t, a, b, inDur = 0.3, outDur = 0.3) {
+  return Math.min(smooth(t, a, a + inDur), 1 - smooth(t, b - outDur, b));
+}
+
+export function mulberry32(seed) {
+  let a = seed >>> 0;
+  return function () {
+    a = (a + 0x6d2b79f5) >>> 0;
+    let t = a;
+    t = Math.imul(t ^ (t >>> 15), t | 1);
+    t ^= t + Math.imul(t ^ (t >>> 7), t | 61);
+    return ((t ^ (t >>> 14)) >>> 0) / 4294967296;
+  };
+}
+
+export function hash1(n) {
+  const s = Math.sin(n * 127.1 + 311.7) * 43758.5453;
+  return s - Math.floor(s);
+}
+
+// Counter that eases toward `to` and keeps visibly ticking while it does.
+export function count(t, a, b, from, to, curve = expoOut) {
+  return Math.round(lerp(from, to, curve(ramp(t, a, b))));
+}

intro-sequence/tools/city/check.py

@@ -0,0 +1,79 @@
+"""Render city/<slug>/check.png: ground imagery (left) and imagery + OSM overlay (right) for alignment QA.
+
+usage: python3 -I tools/city/check.py nyc boston [--crop x y size]
+"""
+import sys, os, json
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from PIL import Image, ImageDraw
+from geo import CITIES, OUT, CACHE
+
+ROADC = [(255, 60, 60), (255, 150, 40), (255, 220, 40), (200, 255, 80), (255, 255, 255), (160, 160, 160)]
+
+
+def render(slug, S=1400, crop=None):
+    d = os.path.join(OUT, slug)
+    h = CITIES[slug]['half']
+    cx, cy, cs = crop if crop else (0, 0, h)  # center and half-size of view in meters
+    g = Image.open(os.path.join(d, 'ground.jpg')).convert('RGB')
+    G = g.size[0]
+    # crop region of ground in pixels
+    l = (cx - cs + h) / (2 * h) * G
+    t = (h - (cy + cs)) / (2 * h) * G
+    r = (cx + cs + h) / (2 * h) * G
+    b = (h - (cy - cs)) / (2 * h) * G
+    base = g.crop((int(l), int(t), int(r), int(b))).resize((S, S), Image.LANCZOS)
+
+    def P(x, y):
+        return ((x - (cx - cs)) / (2 * cs) * S, ((cy + cs) - y) / (2 * cs) * S)
+
+    ov = base.copy()
+    dr = ImageDraw.Draw(ov, 'RGBA')
+    wp = os.path.join(d, 'water.json')
+    if os.path.exists(wp):
+        for poly in json.load(open(wp))['polys']:
+            for k, ring in enumerate(poly):
+                pts = [P(ring[i], ring[i + 1]) for i in range(0, len(ring), 2)]
+                if len(pts) >= 3:
+                    dr.polygon(pts, outline=(60, 160, 255, 255), fill=(30, 90, 255, 70) if k == 0 else None)
+    for bld in json.load(open(os.path.join(d, 'buildings.json')))['b']:
+        hgt = bld[0]
+        pts = [P(bld[i], bld[i + 1]) for i in range(2, len(bld), 2)]
+        a = min(255, 60 + int(hgt))
+        col = (0, 255, 200, 255) if hgt >= 100 else (255, 0, 220, 255)
+        dr.polygon(pts, outline=col, fill=(col[0], col[1], col[2], 40 if hgt < 100 else 90))
+    for rd in json.load(open(os.path.join(d, 'roads.json')))['roads']:
+        pts = [P(rd[i], rd[i + 1]) for i in range(3, len(rd), 2)]
+        dr.line(pts, fill=ROADC[rd[0]] + (230,), width=2 if rd[0] < 3 else 1)
+    rp = os.path.join(d, 'rail.json')
+    if os.path.exists(rp):
+        for ln in json.load(open(rp))['lines']:
+            c = ln[0]
+            col = tuple(int(c[i:i + 2], 16) for i in (1, 3, 5)) + (255,)
+            pts = [P(ln[i], ln[i + 1]) for i in range(1, len(ln), 2)]
+            dr.line(pts, fill=col, width=3)
+    ep = os.path.join(d, 'extra.json')
+    if os.path.exists(ep):
+        for x, y, nm in json.load(open(ep))['helipads']:
+            px, py = P(x, y)
+            dr.ellipse((px - 7, py - 7, px + 7, py + 7), outline=(255, 255, 0, 255), width=3)
+    out = Image.new('RGB', (S * 2 + 10, S), (0, 0, 0))
+    out.paste(base, (0, 0))
+    out.paste(ov, (S + 10, 0))
+    return out
+
+
+if __name__ == '__main__':
+    args = [a for a in sys.argv[1:] if not a.startswith('--')]
+    crop = None
+    if '--crop' in sys.argv:
+        i = sys.argv.index('--crop')
+        crop = tuple(float(v) for v in sys.argv[i + 1:i + 4])
+        args = [a for a in args if a not in sys.argv[i + 1:i + 4]]
+    for slug in args or list(CITIES):
+        im = render(slug, crop=crop)
+        if crop:
+            p = os.path.join(CACHE, f'{slug}_check_crop_{int(crop[0])}_{int(crop[1])}_{int(crop[2])}.png')
+        else:
+            p = os.path.join(OUT, slug, 'check.png')
+        im.save(p, optimize=True)
+        print('wrote', p)

intro-sequence/tools/city/fetch_imagery.py

@@ -0,0 +1,107 @@
+"""Esri World Imagery mosaic -> local ENU square, 4096^2 + 2048^2 JPEG.
+
+usage: python3 -I tools/city/fetch_imagery.py nyc boston [--zoom 17]
+"""
+import sys, os, math, io, time
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from concurrent.futures import ThreadPoolExecutor
+import numpy as np
+import requests
+from PIL import Image
+from scipy.ndimage import map_coordinates
+from geo import CITIES, OUT, CACHE, Frame
+
+URL = 'https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}'
+TS = 256
+N = 4096
+SS = 2  # supersample factor before Lanczos downsample
+
+
+def merc_px(lat, lon, z):
+    s = TS * 2 ** z
+    x = (lon + 180.0) / 360.0 * s
+    lr = np.radians(lat)
+    y = (1.0 - np.log(np.tan(lr) + 1.0 / np.cos(lr)) / math.pi) / 2.0 * s
+    return x, y
+
+
+sess = requests.Session()
+sess.headers['User-Agent'] = 'gods-eye-view-intro/1.0 (film asset build)'
+
+
+def get_tile(z, x, y):
+    d = os.path.join(CACHE, 'tiles', str(z), str(x))
+    os.makedirs(d, exist_ok=True)
+    p = os.path.join(d, f'{y}.jpg')
+    if os.path.exists(p) and os.path.getsize(p) > 0:
+        return p, 'cache'
+    last = None
+    for attempt in range(5):
+        try:
+            r = sess.get(URL.format(z=z, x=x, y=y), timeout=60)
+            if r.status_code == 200 and r.content[:2] in (b'\xff\xd8', b'\x89P'):
+                with open(p, 'wb') as f:
+                    f.write(r.content)
+                return p, 'net'
+            last = f'HTTP {r.status_code} {r.headers.get("content-type")}'
+        except Exception as e:  # noqa
+            last = str(e)[:120]
+        time.sleep(1.5 * (attempt + 1))
+    raise RuntimeError(f'tile {z}/{x}/{y} failed: {last}')
+
+
+def build(slug, z):
+    c = CITIES[slug]
+    F = Frame(**c)
+    h = F.half
+    s, w, n, e = F.bbox(h * 1.02)
+    x0, y0 = merc_px(n, w, z)
+    x1, y1 = merc_px(s, e, z)
+    tx0, ty0 = int(x0 // TS), int(y0 // TS)
+    tx1, ty1 = int(x1 // TS), int(y1 // TS)
+    tiles = [(tx, ty) for ty in range(ty0, ty1 + 1) for tx in range(tx0, tx1 + 1)]
+    print(f'== {slug} z{z}: {tx1-tx0+1}x{ty1-ty0+1} = {len(tiles)} tiles')
+    with ThreadPoolExecutor(8) as ex:
+        res = list(ex.map(lambda t: get_tile(z, t[0], t[1]), tiles))
+    print(f'  net {sum(1 for r in res if r[1]=="net")} cache {sum(1 for r in res if r[1]=="cache")}')
+    W, H = (tx1 - tx0 + 1) * TS, (ty1 - ty0 + 1) * TS
+    mos = np.zeros((H, W, 3), np.uint8)
+    for (tx, ty), (p, _) in zip(tiles, res):
+        im = np.asarray(Image.open(p).convert('RGB'))
+        mos[(ty - ty0) * TS:(ty - ty0 + 1) * TS, (tx - tx0) * TS:(tx - tx0 + 1) * TS] = im
+    M = N * SS
+    t = (np.arange(M) + 0.5) / M
+    xs = -h + 2 * h * t           # east
+    ys = h - 2 * h * t            # north, row 0 at top
+    lon = F.lon0 + xs / F.kx
+    lat = F.lat0 + ys / F.ky
+    px, _ = merc_px(np.full_like(lon, F.lat0), lon, z)
+    _, py = merc_px(lat, np.full_like(lat, F.lon0), z)
+    px = px - tx0 * TS - 0.5      # pixel centers
+    py = py - ty0 * TS - 0.5
+    PX, PY = np.meshgrid(px, py)
+    out = np.empty((M, M, 3), np.uint8)
+    for ch in range(3):
+        out[..., ch] = np.clip(map_coordinates(mos[..., ch].astype(np.float32), [PY, PX], order=1,
+                                               mode='nearest'), 0, 255).astype(np.uint8)
+    del PX, PY
+    img = Image.fromarray(out)
+    if SS != 1:
+        img = img.resize((N, N), Image.LANCZOS)
+    d = os.path.join(OUT, slug)
+    os.makedirs(d, exist_ok=True)
+    img.save(os.path.join(d, 'ground.jpg'), quality=90, optimize=True)
+    img.resize((2048, 2048), Image.LANCZOS).save(os.path.join(d, 'ground_2k.jpg'), quality=90, optimize=True)
+    img.resize((768, 768), Image.LANCZOS).save(os.path.join(CACHE, f'{slug}_ground_preview.jpg'), quality=85)
+    mpp_src = 156543.03392 * math.cos(math.radians(F.lat0)) / 2 ** z
+    print(f'  wrote ground.jpg {os.path.getsize(os.path.join(d, "ground.jpg"))/1e6:.1f}MB; '
+          f'source {mpp_src:.2f} m/px, output {2*h/N:.2f} m/px')
+
+
+if __name__ == '__main__':
+    args = [a for a in sys.argv[1:] if not a.startswith('--')]
+    z = 17
+    if '--zoom' in sys.argv:
+        z = int(sys.argv[sys.argv.index('--zoom') + 1])
+    for slug in args or list(CITIES):
+        build(slug, z)

intro-sequence/tools/city/fetch_osm.py

@@ -0,0 +1,495 @@
+"""Fetch OSM buildings / roads / water / extras for the city scenes and write city/<slug>/*.json.
+
+usage: python3 -I tools/city/fetch_osm.py nyc boston
+"""
+import sys, os, math, re, json
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from geo import (CITIES, OUT, Frame, overpass, rdp, rdp_ring, area, centroid, open_ring,
+                 assemble_rings, clip_polyline, clip_polygon, flat, r1, write_json, dedupe)
+
+FT = 0.3048
+
+
+def parse_len(v):
+    """Parse an OSM length tag to meters. Returns None if unparseable."""
+    if v is None:
+        return None
+    s = str(v).strip().lower().replace(',', '.')
+    s = s.split(';')[0].strip()
+    m = re.match(r"^(\d+(?:\.\d+)?)\s*'\s*(?:(\d+(?:\.\d+)?)\s*\"?)?$", s)  # 12'6"
+    if m:
+        return float(m.group(1)) * FT + (float(m.group(2)) * 0.0254 if m.group(2) else 0)
+    m = re.match(r'^(-?\d+(?:\.\d+)?)\s*(m|meters?|metres?|ft|feet|foot)?$', s)
+    if not m:
+        return None
+    val = float(m.group(1))
+    u = m.group(2) or 'm'
+    if u in ('ft', 'feet', 'foot'):
+        val *= FT
+    return val
+
+
+def parse_num(v):
+    if v is None:
+        return None
+    m = re.match(r'^\s*(\d+(?:\.\d+)?)', str(v).replace(',', '.'))
+    return float(m.group(1)) if m else None
+
+
+HOUSE = {'house', 'detached', 'semidetached_house', 'terrace', 'bungalow', 'cabin', 'shed', 'garage',
+         'garages', 'hut', 'carport', 'static_caravan'}
+
+
+def building_height(t):
+    """Returns (height, min_height, source) where source in h/lv/def."""
+    h = parse_len(t.get('height'))
+    src = 'h'
+    if h is None or h <= 0:
+        lv = parse_num(t.get('building:levels'))
+        if lv is not None and lv > 0:
+            h = lv * 3.2 + (parse_num(t.get('roof:levels')) or 0) * 3.2
+            src = 'lv'
+        else:
+            b = t.get('building', 'yes')
+            h = 7.0 if b in HOUSE else 12.0
+            if b in ('shed', 'garage', 'garages', 'carport', 'hut'):
+                h = 3.5
+            src = 'def'
+    mh = parse_len(t.get('min_height'))
+    if mh is None:
+        ml = parse_num(t.get('building:min_level'))
+        mh = ml * 3.2 if ml else 0.0
+    mh = max(0.0, mh)
+    if mh >= h:
+        mh = 0.0
+    return h, mh, src
+
+
+def ll_list(geom):
+    return [(g['lat'], g['lon']) for g in geom if g is not None]
+
+
+# ------------------------------------------------------------------ buildings
+
+def buildings(slug, F):
+    h = F.half
+    s, w, n, e = F.bbox(h + 60)
+    # tile the bbox to keep each response manageable
+    T = 2 if h > 3000 else 1
+    elems = {}
+    for i in range(T):
+        for j in range(T):
+            ts = s + (n - s) * i / T
+            tn = s + (n - s) * (i + 1) / T
+            tw = w + (e - w) * j / T
+            te = w + (e - w) * (j + 1) / T
+            bb = f'{ts:.6f},{tw:.6f},{tn:.6f},{te:.6f}'
+            q = (f'[out:json][timeout:180];(way["building"]({bb});'
+                 f'relation["building"]["type"="multipolygon"]({bb}););out geom;')
+            print(f' buildings tile {i},{j}')
+            d = overpass(q, f'{slug}_bld_{i}{j}')
+            for el in d['elements']:
+                elems[(el['type'], el['id'])] = el
+    print(f'  {len(elems)} building elements')
+    out = []
+    stats = dict(h=0, lv=0, df=0, dropped_small=0, dropped_out=0, rel_rings=0)
+    for (typ, _id), el in elems.items():
+        t = el.get('tags', {})
+        if t.get('building') in ('no', 'construction_site'):
+            continue
+        rings = []
+        if typ == 'way':
+            if 'geometry' not in el:
+                continue
+            g = ll_list(el['geometry'])
+            if len(g) >= 4 and g[0] == g[-1]:
+                rings.append(g)
+        else:
+            outers = [ll_list(m['geometry']) for m in el.get('members', [])
+                      if m['type'] == 'way' and m.get('role') == 'outer' and 'geometry' in m]
+            rings = assemble_rings(outers)
+            stats['rel_rings'] += len(rings)
+        hgt, mh, src = building_height(t)
+        for g in rings:
+            pts = open_ring([F.xy(la, lo) for la, lo in g])
+            pts = rdp_ring(pts, 0.5)
+            if len(pts) < 3 or abs(area(pts)) < 8:
+                stats['dropped_small'] += 1
+                continue
+            cx, cy = centroid(pts)
+            if abs(cx) > h or abs(cy) > h:
+                stats['dropped_out'] += 1
+                continue
+            stats[{'h': 'h', 'lv': 'lv', 'def': 'df'}[src]] += 1
+            out.append((cx * cx + cy * cy, [r1(hgt), r1(mh)] + flat(pts)))
+    out.sort(key=lambda a: a[0])
+    b = [o[1] for o in out]
+    write_json(os.path.join(OUT, slug, 'buildings.json'), {'count': len(b), 'b': b})
+    hs = sorted(x[0] for x in b)
+    print(f'  buildings {len(b)}  height-src tag={stats["h"]} levels={stats["lv"]} default={stats["df"]} '
+          f'dropped small={stats["dropped_small"]} outside={stats["dropped_out"]}  tallest={hs[-5:]}')
+    return dict(count=len(b), height_from_tag=stats['h'], height_from_levels=stats['lv'],
+                height_default=stats['df'], tallest_m=hs[-1] if hs else None)
+
+
+# ------------------------------------------------------------------ roads
+
+CLS = {'motorway': 0, 'trunk': 0, 'primary': 1, 'secondary': 2, 'tertiary': 3,
+       'residential': 4, 'unclassified': 4, 'service': 5}
+DEF_LANES = {0: 3, 1: 2, 2: 2, 3: 2, 4: 1, 5: 1}
+
+
+def plen(pts):
+    return sum(math.hypot(pts[i + 1][0] - pts[i][0], pts[i + 1][1] - pts[i][1]) for i in range(len(pts) - 1))
+
+
+def roads(slug, F):
+    h = F.half
+    s, w, n, e = F.bbox(h + 100)
+    bb = f'{s:.6f},{w:.6f},{n:.6f},{e:.6f}'
+    q = (f'[out:json][timeout:180];way["highway"~"^(motorway|trunk|primary|secondary|tertiary|residential|'
+         f'unclassified|service|motorway_link|trunk_link|primary_link|secondary_link|tertiary_link)$"]({bb});out geom;')
+    print(' roads')
+    d = overpass(q, f'{slug}_roads')
+    out = []
+    cnt = [0] * 6
+    tunnels = 0
+    short_service = 0
+    for el in d['elements']:
+        t = el.get('tags', {})
+        hw = t['highway']
+        if t.get('area') == 'yes':
+            continue
+        if t.get('tunnel') in ('yes', 'covered') or t.get('layer', '0').startswith('-') and t.get('tunnel'):
+            tunnels += 1
+            continue
+        pts = [F.xy(la, lo) for la, lo in ll_list(el.get('geometry', []))]
+        pts = dedupe(pts)
+        if len(pts) < 2:
+            continue
+        if hw.endswith('_link'):
+            c = 5
+        else:
+            c = CLS[hw]
+        if hw == 'service' and plen(pts) <= 80:
+            short_service += 1
+            continue
+        ow = t.get('oneway', '')
+        oneway = 0
+        if ow in ('yes', '1', 'true'):
+            oneway = 1
+        elif ow == '-1':
+            oneway = 1
+            pts = pts[::-1]
+        elif ow == 'no':
+            oneway = 0
+        elif hw in ('motorway', 'motorway_link') or t.get('junction') in ('roundabout', 'circular'):
+            oneway = 1
+        ln = parse_num(t.get('lanes'))
+        lanes = int(ln) if ln else DEF_LANES[c]
+        for piece in clip_polyline(pts, -h, -h, h, h):
+            piece = rdp(piece, 1.0)
+            if len(piece) < 2 or plen(piece) < 1:
+                continue
+            out.append([c, oneway, lanes] + flat(piece))
+            cnt[c] += 1
+    write_json(os.path.join(OUT, slug, 'roads.json'), {'roads': out})
+    print(f'  roads {len(out)} by class {cnt}  (dropped tunnels {tunnels}, short service {short_service})')
+    return dict(count=len(out), by_class=cnt, dropped_tunnel_ways=tunnels, dropped_short_service=short_service)
+
+
+# ------------------------------------------------------------------ water
+
+def coast_water(slug, F, h):
+    """Build water polygons inside the square from natural=coastline (land left, water right)."""
+    s, w, n, e = F.bbox(h * 1.6)
+    bb = f'{s:.6f},{w:.6f},{n:.6f},{e:.6f}'
+    q = f'[out:json][timeout:180];way["natural"="coastline"]({bb});out geom;'
+    print(' coastline')
+    d = overpass(q, f'{slug}_coast')
+    ways = [[F.xy(la, lo) for la, lo in ll_list(el['geometry'])] for el in d['elements'] if 'geometry' in el]
+    # directional merge into chains
+    chains = []
+    pool = [wy for wy in ways if len(wy) >= 2]
+    while pool:
+        cur = pool.pop()
+        grown = True
+        while grown and cur[0] != cur[-1]:
+            grown = False
+            for i, wy in enumerate(pool):
+                if wy[0] == cur[-1]:
+                    cur = cur + wy[1:]
+                elif wy[-1] == cur[0]:
+                    cur = wy + cur[1:]
+                else:
+                    continue
+                pool.pop(i)
+                grown = True
+                break
+        chains.append(cur)
+    eps = 1e-6
+
+    def on_edge(p):
+        return abs(abs(p[0]) - h) < 1e-3 or abs(abs(p[1]) - h) < 1e-3
+
+    def spos(p):  # clockwise perimeter coordinate from top-left
+        x, y = p
+        if abs(y - h) < 1e-3:
+            return x + h
+        if abs(x - h) < 1e-3:
+            return 2 * h + (h - y)
+        if abs(y + h) < 1e-3:
+            return 4 * h + (h - x)
+        return 6 * h + (y + h)
+
+    corners = [(0.0, (-h, h)), (2 * h, (h, h)), (4 * h, (h, -h)), (6 * h, (-h, -h))]
+    pieces, islands, bad = [], [], 0
+    for ch in chains:
+        closed = ch[0] == ch[-1]
+        inside_all = all(abs(x) <= h and abs(y) <= h for x, y in ch)
+        if closed and inside_all:
+            islands.append(open_ring(ch))
+            continue
+        for pc in clip_polyline(ch, -h, -h, h, h):
+            if on_edge(pc[0]) and on_edge(pc[-1]):
+                pieces.append(pc)
+            else:
+                bad += 1
+    polys = []
+    if pieces:
+        used = [False] * len(pieces)
+        starts = [spos(p[0]) for p in pieces]
+        for k in range(len(pieces)):
+            if used[k]:
+                continue
+            ring = []
+            cur = k
+            guard = 0
+            while True:
+                used[cur] = True
+                ring += pieces[cur]
+                se = spos(pieces[cur][-1])
+                # next entry clockwise from se
+                best, bd = None, None
+                for m in range(len(pieces)):
+                    dd = (starts[m] - se) % (8 * h)
+                    if bd is None or dd < bd:
+                        best, bd = m, dd
+                # add corners passed between se and se+bd
+                for cs, cp in sorted(corners, key=lambda c: (c[0] - se) % (8 * h)):
+                    if 0 < (cs - se) % (8 * h) < bd:
+                        ring.append(cp)
+                cur = best
+                guard += 1
+                if cur == k or guard > len(pieces) + 2:
+                    break
+                if used[cur]:
+                    break
+            polys.append([dedupe(open_ring(ring))])
+    # attach islands (land holes) to the containing water polygon
+    def pip(pt, ring):
+        x, y = pt
+        c = False
+        for i in range(len(ring)):
+            x1, y1 = ring[i]
+            x2, y2 = ring[i - 1]
+            if (y1 > y) != (y2 > y) and x < (x2 - x1) * (y - y1) / (y2 - y1) + x1:
+                c = not c
+        return c
+    for isl in islands:
+        if abs(area(isl)) < 50:
+            continue
+        for p in polys:
+            if pip(isl[0], p[0]):
+                p.append(isl)
+                break
+    print(f'  coastline chains {len(chains)} pieces {len(pieces)} islands {len(islands)} '
+          f'water polys {len(polys)} (unclosed pieces skipped {bad})')
+    return polys, bad
+
+
+def water(slug, F):
+    h = F.half
+    s, w, n, e = F.bbox(h + 50)
+    bb = f'{s:.6f},{w:.6f},{n:.6f},{e:.6f}'
+    q = (f'[out:json][timeout:180];(way["natural"="water"]({bb});relation["natural"="water"]({bb});'
+         f'way["waterway"="riverbank"]({bb});relation["waterway"="riverbank"]({bb}););out geom;')
+    print(' water areas')
+    d = overpass(q, f'{slug}_water')
+    polys = []
+    for el in d['elements']:
+        t = el.get('tags', {})
+        if t.get('water') in ('pond', 'reflecting_pool', 'fountain', 'basin', 'reservoir') and el['type'] == 'way':
+            pass  # keep small ponds too; they are real water
+        if el['type'] == 'way':
+            if 'geometry' not in el:
+                continue
+            g = ll_list(el['geometry'])
+            if g[0] != g[-1]:
+                continue
+            outers, inners = [g], []
+        else:
+            mem = [m for m in el.get('members', []) if m['type'] == 'way' and 'geometry' in m]
+            outers = assemble_rings([ll_list(m['geometry']) for m in mem if m.get('role') == 'outer'])
+            inners = assemble_rings([ll_list(m['geometry']) for m in mem if m.get('role') == 'inner'])
+        inn_xy = [open_ring([F.xy(*p) for p in r]) for r in inners]
+        for o in outers:
+            ring = open_ring([F.xy(*p) for p in o])
+            ring = clip_polygon(ring, -h, -h, h, h)
+            ring = rdp_ring(open_ring(ring), 1.0)
+            if len(ring) < 3 or abs(area(ring)) < 20:
+                continue
+            p = [ring]
+            for ir in inn_xy:
+                ir2 = rdp_ring(open_ring(clip_polygon(ir, -h, -h, h, h)), 1.0)
+                if len(ir2) >= 3 and abs(area(ir2)) >= 20:
+                    p.append(ir2)
+            polys.append(('water', p))
+    n_area = len(polys)
+    cpolys, bad = coast_water(slug, F, h)
+    for p in cpolys:
+        p2 = [rdp_ring(r, 1.0) for r in p]
+        p2 = [r for r in p2 if len(r) >= 3]
+        if p2:
+            polys.append(('coast', p2))
+    out = [[flat(r) for r in p] for _, p in polys]
+    src = [s_ for s_, _ in polys]
+    write_json(os.path.join(OUT, slug, 'water.json'),
+               {'count': len(out), 'format': 'polys[i] = [outerRing, holeRing...], rings flat x,y', 'src': src,
+                'polys': out})
+    print(f'  water polys {len(out)} (osm water areas {n_area}, coastline-derived {len(cpolys)})')
+    return dict(count=len(out), water_areas=n_area, coastline_polys=len(cpolys), coastline_unclosed_pieces=bad)
+
+
+# ------------------------------------------------------------------ extras
+
+KNOWN_HELI = ['Downtown Manhattan Heliport', 'West 30th Street Heliport', 'East 34th Street Heliport']
+
+
+def nyc_extra(slug, F):
+    s, w, n, e = F.bbox(F.half + 2000)
+    bb = f'{s:.6f},{w:.6f},{n:.6f},{e:.6f}'
+    q = (f'[out:json][timeout:180];(nwr["aeroway"~"^(helipad|heliport)$"]({bb});'
+         f'nwr["name"~"heliport|helistop|helipad",i]({bb}););out center tags;')
+    print(' helipads')
+    d = overpass(q, f'{slug}_heli2')
+    pads = []
+    for el in d['elements']:
+        t = el.get('tags', {})
+        if el['type'] == 'node':
+            la, lo = el['lat'], el['lon']
+        else:
+            c = el.get('center')
+            if not c:
+                continue
+            la, lo = c['lat'], c['lon']
+        x, y = F.xy(la, lo)
+        name = t.get('name') or t.get('operator') or ''
+        kind = t.get('aeroway') or ('heliport' if 'heliport' in name.lower() else 'named')
+        pads.append(dict(x=r1(x), y=r1(y), name=name, kind=kind, ref=t.get('ref', ''), osm=f"{el['type']}/{el['id']}",
+                         tags={k: v for k, v in t.items() if k in ('aeroway', 'faa', 'operator', 'man_made', 'amenity')},
+                         inside=abs(x) <= F.half and abs(y) <= F.half))
+    pads.sort(key=lambda p: (p['kind'] != 'heliport', p['x'] ** 2 + p['y'] ** 2))
+    for p in pads:
+        print(f"   {p['kind']:9s} {p['x']:8.1f} {p['y']:8.1f} {'in ' if p['inside'] else 'OUT'} {p['name']}")
+    found = {k: [p for p in pads if p['kind'] == 'heliport' and k.split()[0].lower() in p['name'].lower()
+                 and 'heliport' in p['name'].lower()] for k in KNOWN_HELI}
+    helipads = [[p['x'], p['y'], p['name'] or (f"{p['kind']} {p['ref']}".strip())] for p in pads]
+    write_json(os.path.join(OUT, slug, 'extra.json'),
+               {'helipads': helipads,
+                'detail': pads,
+                'note': 'aeroway=helipad|heliport from OSM in a bbox 2 km wider than the scene; '
+                        'detail[].inside says whether the point is inside the scene square'})
+    return dict(helipad_points=len(pads), named_heliports={k: (v[0]['x'], v[0]['y'], v[0]['inside']) if v else None
+                                                           for k, v in found.items()})
+
+
+def boston_rail(slug, F):
+    h = F.half
+    s, w, n, e = F.bbox(h + 100)
+    bb = f'{s:.6f},{w:.6f},{n:.6f},{e:.6f}'
+    q = (f'[out:json][timeout:180];(relation["route"~"^(subway|light_rail|train|tram)$"]({bb});'
+         f'way["railway"~"^(subway|light_rail|rail|tram)$"]({bb}););out geom;')
+    print(' rail')
+    d = overpass(q, f'{slug}_rail')
+    ways = {el['id']: el for el in d['elements'] if el['type'] == 'way'}
+    rels = [el for el in d['elements'] if el['type'] == 'relation']
+    lines, seen = [], set()
+    rel_names = []
+    for r in rels:
+        t = r.get('tags', {})
+        col = (t.get('colour') or t.get('color') or '').strip()
+        if not re.match(r'^#?[0-9a-fA-F]{6}$', col):
+            col = {'subway': '#888888', 'light_rail': '#00843D', 'tram': '#00843D', 'train': '#80276C'}[t['route']]
+        if not col.startswith('#'):
+            col = '#' + col
+        col = col.upper()
+        rel_names.append(f"{t.get('route')}:{t.get('name', t.get('ref', ''))}:{col}")
+        for m in r.get('members', []):
+            if m['type'] != 'way' or 'geometry' not in m or m.get('role') in ('platform', 'stop'):
+                continue
+            wt = ways.get(m['ref'], {}).get('tags', {})
+            if wt.get('public_transport') or wt.get('railway') == 'platform':
+                continue
+            key = (m['ref'], col)
+            if key in seen:
+                continue
+            seen.add(key)
+            pts = [F.xy(la, lo) for la, lo in ll_list(m['geometry'])]
+            for pc in clip_polyline(dedupe(pts), -h, -h, h, h):
+                pc = rdp(pc, 1.0)
+                if len(pc) >= 2:
+                    lines.append([col] + flat(pc))
+    covered = {k[0] for k in seen}
+    extra = 0
+    for wid, el in ways.items():
+        t = el.get('tags', {})
+        if wid in covered or t.get('service') or 'geometry' not in el:
+            continue
+        pts = [F.xy(la, lo) for la, lo in ll_list(el['geometry'])]
+        for pc in clip_polyline(dedupe(pts), -h, -h, h, h):
+            pc = rdp(pc, 1.0)
+            if len(pc) >= 2:
+                lines.append(['#7F7F7F'] + flat(pc))
+                extra += 1
+    write_json(os.path.join(OUT, slug, 'rail.json'),
+               {'lines': lines, 'routes': sorted(set(rel_names)),
+                'note': 'OSM route relations (subway/light_rail/train/tram) colour tags; #7F7F7F = railway way not in any route relation'})
+    print(f'  rail lines {len(lines)} from {len(rels)} route relations (+{extra} unassigned way pieces)')
+    for nm in sorted(set(rel_names)):
+        print('   ', nm)
+    return dict(polylines=len(lines), route_relations=len(rels), unassigned_pieces=extra)
+
+
+def main():
+    slugs = sys.argv[1:] or list(CITIES)
+    report = {}
+    for slug in slugs:
+        c = CITIES[slug]
+        F = Frame(**c)
+        print(f'== {slug}')
+        write_json(os.path.join(OUT, slug, 'meta.json'),
+                   {'slug': slug, 'name': c['name'], 'lat0': c['lat0'], 'lon0': c['lon0'], 'half': c['half'],
+                    'frame': 'ENU m',
+                    'projection': 'x=(lon-lon0)*cos(lat0)*111320, y=(lat-lat0)*110540',
+                    'source': 'OpenStreetMap contributors (ODbL) via Overpass; imagery Esri World Imagery'})
+        r = {}
+        r['buildings'] = buildings(slug, F)
+        r['roads'] = roads(slug, F)
+        try:
+            r['water'] = water(slug, F)
+        except Exception as ex:  # noqa
+            print('  WATER FAILED', ex)
+            r['water'] = f'failed: {ex}'
+        if slug == 'nyc':
+            r['extra'] = nyc_extra(slug, F)
+        if slug == 'boston':
+            r['rail'] = boston_rail(slug, F)
+        report[slug] = r
+    print(json.dumps(report, indent=1))
+    with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'cache', 'osm_report.json'), 'w') as f:
+        json.dump(report, f, indent=1)
+
+
+if __name__ == '__main__':
+    main()

intro-sequence/tools/city/geo.py

@@ -0,0 +1,288 @@
+"""Shared helpers for the city scene geodata fetchers (ENU frame, Overpass, geometry)."""
+import json, math, os, time, hashlib
+import requests
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+ROOT = os.path.abspath(os.path.join(HERE, '..', '..'))
+OUT = os.path.join(ROOT, 'city')
+CACHE = os.path.join(HERE, 'cache')
+os.makedirs(CACHE, exist_ok=True)
+
+CITIES = {
+    'nyc': dict(name='New York — Midtown / Chelsea / Lower Manhattan', lat0=40.7400, lon0=-73.9900, half=3500),
+    'boston': dict(name='Boston — Downtown / Back Bay / Cambridge / Seaport', lat0=42.3555, lon0=-71.0605, half=3200),
+}
+
+OVERPASS = [
+    'https://overpass-api.de/api/interpreter',
+    'https://overpass.kumi.systems/api/interpreter',
+    'https://overpass.private.coffee/api/interpreter',
+    'https://maps.mail.ru/osm/tools/overpass/api/interpreter',
+]
+
+
+class Frame:
+    def __init__(self, lat0, lon0, half, **_):
+        self.lat0, self.lon0, self.half = lat0, lon0, half
+        self.kx = math.cos(math.radians(lat0)) * 111320.0
+        self.ky = 110540.0
+
+    def xy(self, lat, lon):
+        return ((lon - self.lon0) * self.kx, (lat - self.lat0) * self.ky)
+
+    def ll(self, x, y):
+        return (self.lat0 + y / self.ky, self.lon0 + x / self.kx)
+
+    def bbox(self, half=None):
+        h = self.half if half is None else half
+        s, w = self.ll(-h, -h)
+        n, e = self.ll(h, h)
+        return s, w, n, e
+
+
+def overpass(query, tag):
+    """Run an Overpass query, caching the raw JSON response under cache/osm_<tag>.json."""
+    path = os.path.join(CACHE, f'osm_{tag}.json')
+    if os.path.exists(path):
+        with open(path) as f:
+            return json.load(f)
+    last = None
+    for attempt in range(8):
+        for url in OVERPASS:
+            try:
+                t = time.time()
+                r = requests.post(url, data={'data': query}, timeout=400)
+                if r.status_code != 200:
+                    last = f'{url} HTTP {r.status_code}'
+                    print('  overpass fail', last)
+                    continue
+                d = r.json()
+                if 'remark' in d and 'error' in d.get('remark', '').lower():
+                    last = f'{url} remark {d["remark"][:200]}'
+                    print('  overpass remark', last)
+                    continue
+                print(f'  overpass ok {url} {len(r.content)/1e6:.1f}MB {time.time()-t:.0f}s {len(d["elements"])} el')
+                with open(path, 'w') as f:
+                    json.dump(d, f)
+                return d
+            except Exception as e:  # noqa
+                last = f'{url} {type(e).__name__}: {str(e)[:200]}'
+                print('  overpass fail', last)
+        time.sleep(15 + 15 * attempt)
+    raise RuntimeError('all overpass endpoints failed: ' + str(last))
+
+
+# ---------------- geometry ----------------
+
+def rdp(pts, eps):
+    """Douglas-Peucker on an open polyline (list of (x,y))."""
+    n = len(pts)
+    if n < 3:
+        return list(pts)
+    keep = [False] * n
+    keep[0] = keep[-1] = True
+    stack = [(0, n - 1)]
+    while stack:
+        a, b = stack.pop()
+        ax, ay = pts[a]
+        bx, by = pts[b]
+        dx, dy = bx - ax, by - ay
+        L = math.hypot(dx, dy)
+        dmax, idx = -1.0, -1
+        for i in range(a + 1, b):
+            px, py = pts[i]
+            if L < 1e-9:
+                d = math.hypot(px - ax, py - ay)
+            else:
+                d = abs(dx * (ay - py) - dy * (ax - px)) / L
+            if d > dmax:
+                dmax, idx = d, i
+        if dmax > eps and idx > 0:
+            keep[idx] = True
+            stack.append((a, idx))
+            stack.append((idx, b))
+    return [p for p, k in zip(pts, keep) if k]
+
+
+def rdp_ring(ring, eps):
+    """Douglas-Peucker for a closed ring given without the repeated closing vertex."""
+    n = len(ring)
+    if n < 4:
+        return list(ring)
+    # split at vertex 0 and the vertex farthest from it
+    x0, y0 = ring[0]
+    far = max(range(n), key=lambda i: (ring[i][0] - x0) ** 2 + (ring[i][1] - y0) ** 2)
+    a = rdp(ring[0:far + 1], eps)
+    b = rdp(ring[far:] + [ring[0]], eps)
+    return a[:-1] + b[:-1]
+
+
+def area(ring):
+    s = 0.0
+    n = len(ring)
+    for i in range(n):
+        x1, y1 = ring[i]
+        x2, y2 = ring[(i + 1) % n]
+        s += x1 * y2 - x2 * y1
+    return s / 2.0
+
+
+def centroid(ring):
+    a = area(ring)
+    if abs(a) < 1e-9:
+        xs = [p[0] for p in ring]
+        ys = [p[1] for p in ring]
+        return sum(xs) / len(xs), sum(ys) / len(ys)
+    cx = cy = 0.0
+    n = len(ring)
+    for i in range(n):
+        x1, y1 = ring[i]
+        x2, y2 = ring[(i + 1) % n]
+        c = x1 * y2 - x2 * y1
+        cx += (x1 + x2) * c
+        cy += (y1 + y2) * c
+    return cx / (6 * a), cy / (6 * a)
+
+
+def dedupe(pts):
+    out = []
+    for p in pts:
+        if not out or p != out[-1]:
+            out.append(p)
+    return out
+
+
+def open_ring(pts):
+    pts = dedupe(pts)
+    if len(pts) > 1 and pts[0] == pts[-1]:
+        pts = pts[:-1]
+    return pts
+
+
+def assemble_rings(ways):
+    """Join way coordinate lists (lists of (lat,lon) tuples) into closed rings by matching endpoints."""
+    rings = []
+    pool = [list(w) for w in ways if len(w) >= 2]
+    while pool:
+        cur = pool.pop()
+        changed = True
+        while cur[0] != cur[-1] and changed:
+            changed = False
+            for i, w in enumerate(pool):
+                if w[0] == cur[-1]:
+                    cur = cur + w[1:]
+                elif w[-1] == cur[-1]:
+                    cur = cur + w[::-1][1:]
+                elif w[-1] == cur[0]:
+                    cur = w + cur[1:]
+                elif w[0] == cur[0]:
+                    cur = w[::-1] + cur[1:]
+                else:
+                    continue
+                pool.pop(i)
+                changed = True
+                break
+        if cur[0] == cur[-1] and len(cur) >= 4:
+            rings.append(cur)
+    return rings
+
+
+def clip_polyline(pts, xmin, ymin, xmax, ymax):
+    """Clip a polyline to a rectangle (Liang-Barsky per segment); returns list of pieces."""
+    pieces, cur = [], []
+
+    def inside(p):
+        return xmin <= p[0] <= xmax and ymin <= p[1] <= ymax
+
+    for i in range(len(pts) - 1):
+        (x1, y1), (x2, y2) = pts[i], pts[i + 1]
+        dx, dy = x2 - x1, y2 - y1
+        t0, t1 = 0.0, 1.0
+        ok = True
+        for p, q in ((-dx, x1 - xmin), (dx, xmax - x1), (-dy, y1 - ymin), (dy, ymax - y1)):
+            if p == 0:
+                if q < 0:
+                    ok = False
+                    break
+            else:
+                t = q / p
+                if p < 0:
+                    if t > t1:
+                        ok = False
+                        break
+                    t0 = max(t0, t)
+                else:
+                    if t < t0:
+                        ok = False
+                        break
+                    t1 = min(t1, t)
+        if not ok:
+            if cur:
+                pieces.append(cur)
+                cur = []
+            continue
+        a = (x1, y1) if t0 == 0.0 else (x1 + t0 * dx, y1 + t0 * dy)
+        b = (x2, y2) if t1 == 1.0 else (x1 + t1 * dx, y1 + t1 * dy)
+        if not cur:
+            cur = [a, b]
+        else:
+            if cur[-1] != a:
+                pieces.append(cur)
+                cur = [a, b]
+            else:
+                cur.append(b)
+        if t1 < 1.0:
+            pieces.append(cur)
+            cur = []
+    if cur:
+        pieces.append(cur)
+    return [dedupe(p) for p in pieces if len(dedupe(p)) >= 2]
+
+
+def clip_polygon(ring, xmin, ymin, xmax, ymax):
+    """Sutherland-Hodgman clip of a ring to a rectangle."""
+    def clip(poly, inside, inter):
+        out = []
+        n = len(poly)
+        for i in range(n):
+            cur, prev = poly[i], poly[i - 1]
+            if inside(cur):
+                if not inside(prev):
+                    out.append(inter(prev, cur))
+                out.append(cur)
+            elif inside(prev):
+                out.append(inter(prev, cur))
+        return out
+
+    def ix(xc):
+        return lambda p, q: (xc, p[1] + (q[1] - p[1]) * (xc - p[0]) / (q[0] - p[0]))
+
+    def iy(yc):
+        return lambda p, q: (p[0] + (q[0] - p[0]) * (yc - p[1]) / (q[1] - p[1]), yc)
+
+    poly = list(ring)
+    for ins, inter in ((lambda p: p[0] >= xmin, ix(xmin)), (lambda p: p[0] <= xmax, ix(xmax)),
+                       (lambda p: p[1] >= ymin, iy(ymin)), (lambda p: p[1] <= ymax, iy(ymax))):
+        if not poly:
+            break
+        poly = clip(poly, ins, inter)
+    return dedupe(poly)
+
+
+def r1(v):
+    return round(v, 1)
+
+
+def flat(pts):
+    out = []
+    for x, y in pts:
+        out.append(r1(x))
+        out.append(r1(y))
+    return out
+
+
+def write_json(path, obj):
+    os.makedirs(os.path.dirname(path), exist_ok=True)
+    with open(path, 'w') as f:
+        json.dump(obj, f, separators=(',', ':'))
+    print(f'  wrote {os.path.relpath(path, ROOT)} {os.path.getsize(path)/1e6:.2f}MB')

intro-sequence/tools/city2/build_scene.py

@@ -0,0 +1,188 @@
+"""Build real-geodata scene packs.  usage: python3 build_scene.py lax|bragg|everest [steps...]
+steps: osm ground elev check (default all)"""
+import json
+import os
+import sys
+
+import numpy as np
+from PIL import Image, ImageDraw
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+import common as C  # noqa
+
+SCENES = {
+    "lax": dict(name="Los Angeles International Airport", lat0=33.9425, lon0=-118.4081, half=3500, z=17),
+    "bragg": dict(name="Fort Bragg, North Carolina", lat0=35.1580, lon0=-79.0090, half=6000, z=16),
+    "everest": dict(name="Mount Everest / Khumbu", lat0=27.9881, lon0=86.9250, half=15000, z=15),
+}
+
+NT = {"lax": 4, "bragg": 6}
+AERO_Q = '[out:json][timeout:600];nwr["aeroway"~"^(runway|taxiway|apron|terminal|gate|parking_position)$"]({bb});out geom;'
+BLDG_Q = '[out:json][timeout:300];(way["building"]({bb});relation["building"]({bb}););out geom;'
+ROAD_Q = ('[out:json][timeout:300];way["highway"~"^(motorway|trunk|primary|secondary|tertiary|'
+          'residential|unclassified|living_street|motorway_link|trunk_link|primary_link|secondary_link|tertiary_link|service)$"]({bb});out geom;')
+MIL_Q = '[out:json][timeout:600];(way["landuse"="military"]({bb});relation["landuse"="military"]({bb});way["military"]({bb});relation["military"]({bb}););out geom;'
+PEAK_Q = '[out:json][timeout:300];node["natural"="peak"]({bb});out;'
+
+
+def step_osm(f, slug):
+    bb = f.bbox_str()
+    if slug in ("lax", "bragg"):
+        aero = C.build_aeroway(f, C.overpass(AERO_Q.format(bb=bb), f"{slug}_aero"))
+        if slug == "lax":
+            C.wjson(os.path.join(f.out, "aeroway.json"), aero)
+        else:
+            mil = C.overpass(MIL_Q.format(bb=bb), f"{slug}_mil")
+            polys = []
+            for el in mil["elements"]:
+                tags = el.get("tags", {})
+                for ring in C.outer_rings(el, f):
+                    name = tags.get("name") or (f"[{tags['military']}]" if "military" in tags else "")
+                    polys.append([name] + C.flat(C.dp_ring(ring, 2.0)))
+            names = sorted({p[0] for p in polys if p[0]})
+            print(f"  military polygons: {len(polys)}; names: {names[:40]}")
+            out = {"military": polys, "runways": aero["runways"], "taxiways": aero["taxiways"],
+                   "aprons": aero["aprons"], "apronNames": aero["apronNames"], "terminals": aero["terminals"],
+                   "gates": aero["gates"], "parking": aero["parking"]}
+            C.wjson(os.path.join(f.out, "military.json"), out)
+        C.wjson(os.path.join(f.out, "buildings.json"), C.build_buildings(f, C.overpass_tiled(f, BLDG_Q, f"{slug}_bldg", NT[slug])))
+        C.wjson(os.path.join(f.out, "roads.json"), C.build_roads(f, C.overpass_tiled(f, ROAD_Q, f"{slug}_roads", NT[slug] // 2)))
+    else:
+        d = C.overpass(PEAK_Q.format(bb=bb), f"{slug}_peaks")
+        peaks = []
+        skipped = 0
+        for el in d["elements"]:
+            t = el.get("tags", {})
+            name = t.get("name:en") or t.get("name")
+            ele = t.get("ele")
+            if not name or not ele:
+                skipped += 1
+                continue
+            try:
+                s = ele.lower().replace(",", ".").strip()
+                v = float(s.replace("ft", "").replace("m", "").strip().split()[0].split(";")[0])
+                if "ft" in s:
+                    v *= 0.3048
+            except ValueError:
+                skipped += 1
+                continue
+            x, y = f.xy(el["lon"], el["lat"])
+            peaks.append([C.r1(x), C.r1(y), C.r1(v), name])
+        peaks.sort(key=lambda p: -p[2])
+        print(f"  peaks with name+ele: {len(peaks)} (skipped {skipped} lacking name/ele); top: {peaks[:6]}")
+        C.wjson(os.path.join(f.out, "peaks.json"), peaks)
+
+
+def step_elev(f):
+    z = 12
+    url = "https://s3.amazonaws.com/elevation-tiles-prod/terrarium/{z}/{x}/{y}.png"
+    mos, ox, oy, nf = C.mosaic(f, z, url, "terrarium", "png", "RGB", pad_m=1500)
+    if nf:
+        print(f"  WARNING: {nf} terrarium tiles missing")
+    m = mos.astype(np.float32)
+    h = m[..., 0] * 256 + m[..., 1] + m[..., 2] / 256 - 32768
+    N = 1024
+    e = C.reproject(f, h[..., None], ox, oy, z, N)[..., 0].astype("<f4")
+    e.tofile(os.path.join(f.out, "elev.f32"))
+    meta = {"size": N, "min": C.r1(e.min()), "max": C.r1(e.max()), "half": f.half,
+            "source": "AWS Terrain Tiles terrarium z12", "rowOrder": "row0=north", "dtype": "float32le"}
+    C.wjson(os.path.join(f.out, "elev_meta.json"), meta)
+    print(f"  elev min {e.min():.1f} max {e.max():.1f}")
+    # hillshade
+    cell = 2 * f.half / N
+    gy, gx = np.gradient(e.astype(np.float64), cell)  # gy: d/drow (southward)
+    dzdx, dzdy = gx, -gy
+    az, alt = np.radians(315), np.radians(45)
+    slope = np.arctan(np.hypot(dzdx, dzdy))
+    aspect = np.arctan2(-dzdx, -dzdy)  # direction of steepest descent... simple form
+    lx, ly, lz = np.sin(az) * np.cos(alt), np.cos(az) * np.cos(alt), np.sin(alt)
+    nx, ny, nz = -dzdx, -dzdy, np.ones_like(dzdx)
+    nn = np.sqrt(nx * nx + ny * ny + 1)
+    shade = np.clip((nx * lx + ny * ly + nz * lz) / nn, 0, 1)
+    t = (e - e.min()) / max(1, e.max() - e.min())
+    rgb = np.stack([0.35 + 0.65 * t, 0.45 + 0.55 * t, 0.55 + 0.45 * t], -1) * shade[..., None]
+    Image.fromarray((np.clip(rgb, 0, 1) * 255).astype(np.uint8)).save(os.path.join(f.out, "elev_preview.png"))
+    print("  wrote elev_preview.png")
+
+
+def step_check(f, slug):
+    N = 2048
+    im = C.check_canvas(f)
+    dr = ImageDraw.Draw(im, "RGBA")
+    P = lambda a: C.to_px(f, a, N)  # noqa
+    if slug in ("lax", "bragg"):
+        roads = json.load(open(os.path.join(f.out, "roads.json")))["roads"]
+        col = {0: (255, 60, 60, 230), 1: (255, 160, 40, 220), 2: (255, 230, 60, 200), 3: (200, 255, 120, 180),
+               4: (160, 200, 255, 150), 5: (180, 180, 180, 120)}
+        for r in roads:
+            dr.line(P(r[3:]), fill=col[r[0]], width=2 if r[0] < 3 else 1)
+        bl = json.load(open(os.path.join(f.out, "buildings.json")))["b"]
+        for b in bl:
+            pts = P(b[2:])
+            if len(pts) >= 3:
+                dr.polygon(pts, outline=(0, 255, 255, 200))
+        aero = json.load(open(os.path.join(f.out, "aeroway.json" if slug == "lax" else "military.json")))
+        if slug == "bragg":
+            for m in aero["military"]:
+                dr.polygon(P(m[1:]), outline=(255, 0, 255, 255))
+        for a in aero["aprons"]:
+            dr.polygon(P(a), outline=(255, 255, 255, 200))
+        for t in aero["taxiways"]:
+            dr.line(P(t), fill=(255, 255, 0, 230), width=1)
+        for rw in aero["runways"]:
+            w = max(2, int(rw[0] / (2 * f.half) * N))
+            dr.line(P(rw[2:6]), fill=(255, 40, 40, 110), width=w)
+            dr.line(P(rw[2:6]), fill=(255, 255, 255, 255), width=1)
+        for t in aero["terminals"]:
+            dr.polygon(P(t[1:]), outline=(255, 120, 0, 255))
+        for g in aero["gates"]:
+            (x, y), = P(g[:2])
+            dr.ellipse([x - 2, y - 2, x + 2, y + 2], fill=(0, 255, 0, 255))
+    else:
+        peaks = json.load(open(os.path.join(f.out, "peaks.json")))
+        for x0, y0, ele, name in peaks:
+            (x, y), = P([x0, y0])
+            dr.ellipse([x - 4, y - 4, x + 4, y + 4], outline=(255, 60, 60, 255), width=2)
+            if ele > 6000:
+                dr.text((x + 6, y - 6), f"{name} {ele:.0f}", fill=(255, 255, 255, 255))
+        # contour-ish overlay from DEM to check imagery/DEM alignment
+        e = np.fromfile(os.path.join(f.out, "elev.f32"), "<f4").reshape(1024, 1024)
+        e2 = np.asarray(Image.fromarray(e).resize((N, N), Image.BILINEAR))
+        band = (np.floor(e2 / 500) % 2).astype(np.int8)
+        edge = (np.abs(np.diff(band, axis=0, prepend=band[:1])) + np.abs(np.diff(band, axis=1, prepend=band[:, :1]))) > 0
+        arr = np.asarray(im).copy()
+        arr[edge] = (0.4 * arr[edge] + 0.6 * np.array([0, 255, 255])).astype(np.uint8)
+        im = Image.fromarray(arr)
+        dr = ImageDraw.Draw(im, "RGBA")
+        for x0, y0, ele, name in peaks:
+            (x, y), = P([x0, y0])
+            dr.ellipse([x - 4, y - 4, x + 4, y + 4], outline=(255, 60, 60, 255), width=2)
+            if ele > 6500:
+                dr.text((x + 6, y - 6), f"{name} {ele:.0f}", fill=(255, 255, 255, 255))
+    p = os.path.join(f.out, "check.png")
+    im.save(p)
+    print(f"  wrote {p}")
+
+
+def main():
+    slug = sys.argv[1]
+    steps = sys.argv[2:] or ["osm", "ground", "elev", "check"]
+    s = SCENES[slug]
+    f = C.Frame(slug, s["name"], s["lat0"], s["lon0"], s["half"])
+    f.write_meta()
+    print(f"== {slug} bbox {f.bbox_str()}")
+    if "osm" in steps:
+        step_osm(f, slug)
+    if "ground" in steps:
+        C.build_ground(f, s["z"])
+    if "ground_s2" in steps:
+        # alternative uniform real imagery (EOX Sentinel-2 cloudless 2020) — Esri is a patchwork here
+        C.build_ground(f, 14, C.EOX_S2, "eox_s2", "ground_s2")
+    if "elev" in steps and slug == "everest":
+        step_elev(f)
+    if "check" in steps:
+        step_check(f, slug)
+
+
+if __name__ == "__main__":
+    main()

intro-sequence/tools/city2/common.py

@@ -0,0 +1,571 @@
+"""Shared helpers for real-geodata scene builds (city2).
+
+Local frame: ENU metres relative to (lat0, lon0):
+  x = (lon - lon0) * cos(lat0) * 111320
+  y = (lat - lat0) * 110540
+"""
+import hashlib
+import io
+import json
+import math
+import os
+import sys
+import time
+from concurrent.futures import ThreadPoolExecutor
+
+import numpy as np
+import requests
+from PIL import Image
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+CACHE = os.path.join(HERE, "cache")
+CITY = os.path.abspath(os.path.join(HERE, "..", "..", "city"))
+os.makedirs(CACHE, exist_ok=True)
+
+OVERPASS = [
+    "https://overpass.kumi.systems/api/interpreter",
+    "https://overpass.private.coffee/api/interpreter",
+    "https://maps.mail.ru/osm/tools/overpass/api/interpreter",
+    "https://overpass-api.de/api/interpreter",
+]
+UA = {"User-Agent": "gods-eye-view-intro/1.0 (cinematic geodata build)"}
+
+Image.MAX_IMAGE_PIXELS = None
+
+
+class Frame:
+    def __init__(self, slug, name, lat0, lon0, half):
+        self.slug, self.name, self.lat0, self.lon0, self.half = slug, name, lat0, lon0, half
+        self.kx = math.cos(math.radians(lat0)) * 111320.0
+        self.ky = 110540.0
+        self.out = os.path.join(CITY, slug)
+        os.makedirs(self.out, exist_ok=True)
+
+    def xy(self, lon, lat):
+        return (lon - self.lon0) * self.kx, (lat - self.lat0) * self.ky
+
+    def ll(self, x, y):
+        return self.lon0 + x / self.kx, self.lat0 + y / self.ky
+
+    def bbox(self, pad=0.0):
+        """(south, west, north, east)"""
+        h = self.half + pad
+        return (self.lat0 - h / self.ky, self.lon0 - h / self.kx,
+                self.lat0 + h / self.ky, self.lon0 + h / self.kx)
+
+    def bbox_str(self, pad=0.0):
+        s, w, n, e = self.bbox(pad)
+        return f"{s:.6f},{w:.6f},{n:.6f},{e:.6f}"
+
+    def write_meta(self):
+        meta = {"slug": self.slug, "name": self.name, "lat0": self.lat0, "lon0": self.lon0,
+                "half": self.half, "frame": "ENU m"}
+        wjson(os.path.join(self.out, "meta.json"), meta)
+
+    def geom_xy(self, geom):
+        """list of {lat,lon} -> Nx2 float array in local metres"""
+        a = np.array([[g["lon"], g["lat"]] for g in geom if g is not None], dtype=np.float64)
+        if len(a) == 0:
+            return np.zeros((0, 2))
+        return np.stack([(a[:, 0] - self.lon0) * self.kx, (a[:, 1] - self.lat0) * self.ky], 1)
+
+
+def wjson(path, obj):
+    with open(path, "w") as f:
+        json.dump(obj, f, separators=(",", ":"))
+    print(f"  wrote {path} ({os.path.getsize(path)/1e6:.2f} MB)")
+
+
+def r1(v):
+    return round(float(v), 1)
+
+
+def flat(arr):
+    return [r1(v) for v in np.asarray(arr).reshape(-1)]
+
+
+# ---------------------------------------------------------------- Overpass
+def overpass(query, tag):
+    key = hashlib.sha1(query.encode()).hexdigest()[:12]
+    path = os.path.join(CACHE, f"overpass_{tag}_{key}.json")
+    if os.path.exists(path):
+        with open(path) as f:
+            return json.load(f)
+    last = None
+    for attempt in range(10):
+        for url in OVERPASS:
+            try:
+                print(f"  overpass {tag} -> {url}", flush=True)
+                t = time.time()
+                r = requests.get(url, params={"data": query}, headers=UA, timeout=900)
+                if r.status_code != 200:
+                    last = f"{url}: HTTP {r.status_code} {r.text[:200]}"
+                    print("   ", last)
+                    continue
+                d = r.json()
+                rem = d.get("remark", "")
+                if rem and ("runtime error" in rem or "timed out" in rem or "out of memory" in rem):
+                    last = f"{url}: remark {rem[:200]}"
+                    print("   ", last)
+                    continue
+                print(f"    {len(d.get('elements', []))} elements in {time.time()-t:.0f}s")
+                with open(path, "w") as f:
+                    json.dump(d, f)
+                return d
+            except Exception as e:  # noqa
+                last = f"{url}: {e}"
+                print("   ", last)
+        time.sleep(30)
+    raise RuntimeError(f"overpass failed for {tag}: {last}")
+
+
+def overpass_tiled(frame, qfmt, tag, n):
+    """Run a query template ({bb} placeholder) over an n x n split of the frame bbox; dedupe elements."""
+    s, w, nn, e = frame.bbox()
+    seen, els = set(), []
+    for i in range(n):
+        for j in range(n):
+            bb = (f"{s + (nn - s) * i / n:.6f},{w + (e - w) * j / n:.6f},"
+                  f"{s + (nn - s) * (i + 1) / n:.6f},{w + (e - w) * (j + 1) / n:.6f}")
+            d = overpass(qfmt.format(bb=bb), f"{tag}_{i}{j}")
+            for el in d["elements"]:
+                k = (el["type"], el["id"])
+                if k not in seen:
+                    seen.add(k)
+                    els.append(el)
+    print(f"  {tag}: {len(els)} unique elements over {n}x{n} tiles")
+    return {"elements": els}
+
+
+# ---------------------------------------------------------------- geometry
+def assemble_rings(ways):
+    """ways: list of Nx2 arrays (open or closed). Returns list of closed rings."""
+    rings = []
+    pending = [w for w in ways if len(w) >= 2]
+    while pending:
+        cur = pending.pop(0)
+        changed = True
+        while not np.allclose(cur[0], cur[-1], atol=1e-3) and changed:
+            changed = False
+            for i, w in enumerate(pending):
+                if np.allclose(cur[-1], w[0], atol=1e-3):
+                    cur = np.vstack([cur, w[1:]])
+                elif np.allclose(cur[-1], w[-1], atol=1e-3):
+                    cur = np.vstack([cur, w[::-1][1:]])
+                elif np.allclose(cur[0], w[-1], atol=1e-3):
+                    cur = np.vstack([w, cur[1:]])
+                elif np.allclose(cur[0], w[0], atol=1e-3):
+                    cur = np.vstack([w[::-1], cur[1:]])
+                else:
+                    continue
+                pending.pop(i)
+                changed = True
+                break
+        if np.allclose(cur[0], cur[-1], atol=1e-3) and len(cur) >= 4:
+            rings.append(cur)
+    return rings
+
+
+def outer_rings(el, frame):
+    """Outer rings (local metres, closed) for a way or multipolygon relation with out geom."""
+    if el["type"] == "way":
+        g = el.get("geometry")
+        if not g:
+            return []
+        a = frame.geom_xy(g)
+        if len(a) >= 4 and np.allclose(a[0], a[-1], atol=1e-3):
+            return [a]
+        return []
+    if el["type"] == "relation":
+        ways = [frame.geom_xy(m["geometry"]) for m in el.get("members", [])
+                if m.get("type") == "way" and m.get("role", "outer") in ("outer", "") and m.get("geometry")]
+        return assemble_rings(ways)
+    return []
+
+
+def dp(pts, eps):
+    """Douglas-Peucker on Nx2 array (iterative)."""
+    n = len(pts)
+    if n < 3:
+        return pts
+    keep = np.zeros(n, bool)
+    keep[0] = keep[-1] = True
+    stack = [(0, n - 1)]
+    while stack:
+        a, b = stack.pop()
+        if b <= a + 1:
+            continue
+        p, q = pts[a], pts[b]
+        seg = pts[a + 1:b]
+        d = q - p
+        L = math.hypot(d[0], d[1])
+        if L < 1e-9:
+            dist = np.hypot(seg[:, 0] - p[0], seg[:, 1] - p[1])
+        else:
+            dist = np.abs(d[0] * (seg[:, 1] - p[1]) - d[1] * (seg[:, 0] - p[0])) / L
+        i = int(np.argmax(dist))
+        if dist[i] > eps:
+            m = a + 1 + i
+            keep[m] = True
+            stack.append((a, m))
+            stack.append((m, b))
+    return pts[keep]
+
+
+def dp_ring(ring, eps):
+    """DP for a closed ring: split at the vertex farthest from ring[0]."""
+    r = ring[:-1] if np.allclose(ring[0], ring[-1]) else ring
+    if len(r) < 4:
+        return r
+    far = int(np.argmax(np.hypot(*(r - r[0]).T)))
+    a = dp(np.vstack([r[:far + 1]]), eps)
+    b = dp(np.vstack([r[far:], r[:1]]), eps)
+    return np.vstack([a[:-1], b[:-1]])  # open ring (no repeated closing vertex)
+
+
+def area(ring):
+    x, y = ring[:, 0], ring[:, 1]
+    return 0.5 * abs(np.dot(x, np.roll(y, -1)) - np.dot(y, np.roll(x, -1)))
+
+
+def poly_len(a):
+    return float(np.sum(np.hypot(*np.diff(a, axis=0).T))) if len(a) > 1 else 0.0
+
+
+def clip_polyline(a, lim):
+    """Split a polyline into runs inside the square |x|,|y|<=lim, cutting segments at the edge."""
+    out, cur = [], []
+    inside = (np.abs(a[:, 0]) <= lim) & (np.abs(a[:, 1]) <= lim)
+
+    def cut(p, q):
+        # point on segment p->q at the square boundary (p inside, q outside)
+        t = 1.0
+        d = q - p
+        for k in range(2):
+            if d[k] > 0 and q[k] > lim:
+                t = min(t, (lim - p[k]) / d[k])
+            elif d[k] < 0 and q[k] < -lim:
+                t = min(t, (-lim - p[k]) / d[k])
+        return p + d * t
+
+    for i in range(len(a)):
+        if inside[i]:
+            if not cur and i > 0:
+                cur.append(cut(a[i], a[i - 1]))
+            cur.append(a[i])
+        else:
+            if cur:
+                cur.append(cut(a[i - 1], a[i]))
+                out.append(np.array(cur))
+                cur = []
+    if cur:
+        out.append(np.array(cur))
+    return [c for c in out if len(c) >= 2]
+
+
+def tag_height(tags, default=10.0):
+    def num(s):
+        try:
+            s = str(s).strip().lower().replace(",", ".")
+            ft = s.endswith("ft") or s.endswith("'")
+            s = s.replace("m", "").replace("ft", "").replace("'", "").strip().split(";")[0].split()[0]
+            v = float(s)
+            return v * 0.3048 if ft else v
+        except Exception:
+            return None
+    h = num(tags["height"]) if "height" in tags else None
+    if h is None and "building:levels" in tags:
+        lv = num(tags["building:levels"])
+        if lv is not None:
+            h = lv * 3.2
+    if h is None or h <= 0:
+        h = default
+    mh = num(tags["min_height"]) if "min_height" in tags else None
+    if mh is None and "building:min_level" in tags:
+        lv = num(tags["building:min_level"])
+        mh = lv * 3.2 if lv is not None else None
+    mh = mh if (mh is not None and 0 <= mh < h) else 0.0
+    return h, mh
+
+
+# ---------------------------------------------------------------- buildings / roads
+def build_buildings(frame, data, min_area=6.0):
+    b = []
+    dropped = 0
+    lim = frame.half
+    for el in data["elements"]:
+        if el["type"] not in ("way", "relation"):
+            continue
+        tags = el.get("tags", {})
+        if "building" not in tags:
+            continue
+        h, mh = tag_height(tags)
+        for ring in outer_rings(el, frame):
+            c = ring[:-1].mean(0)
+            if abs(c[0]) > lim or abs(c[1]) > lim:
+                continue
+            s = dp_ring(ring, 0.5)
+            if len(s) < 3 or area(s) < min_area:
+                dropped += 1
+                continue
+            b.append([r1(h), r1(mh)] + flat(s))
+    print(f"  buildings: {len(b)} kept, {dropped} tiny dropped")
+    return {"count": len(b), "b": b}
+
+
+ROAD_CLASS = {
+    "motorway": 0, "trunk": 0,
+    "primary": 1, "secondary": 2, "tertiary": 3,
+    "residential": 4, "unclassified": 4, "living_street": 4,
+    "motorway_link": 5, "trunk_link": 5, "primary_link": 5, "secondary_link": 5,
+    "tertiary_link": 5, "service": 5,
+}
+DEFAULT_LANES = {0: 3, 1: 2, 2: 2, 3: 2, 4: 1, 5: 1}
+
+
+def build_roads(frame, data):
+    roads = []
+    counts = {}
+    lim = frame.half + 50
+    for el in data["elements"]:
+        if el["type"] != "way" or not el.get("geometry"):
+            continue
+        tags = el.get("tags", {})
+        hw = tags.get("highway")
+        if hw not in ROAD_CLASS:
+            continue
+        cls = ROAD_CLASS[hw]
+        a = frame.geom_xy(el["geometry"])
+        if hw == "service" and poly_len(a) <= 80:
+            continue
+        ow = tags.get("oneway", "")
+        oneway = 0
+        if ow in ("yes", "1", "true") or (hw in ("motorway",) and ow != "no") or tags.get("junction") in ("roundabout", "circular"):
+            oneway = 1
+        elif ow == "-1":
+            oneway = 1
+            a = a[::-1]
+        try:
+            lanes = int(str(tags.get("lanes", "")).split(";")[0])
+        except ValueError:
+            lanes = DEFAULT_LANES[cls] * (1 if oneway else 2) if cls < 4 else (1 if oneway else 2)
+        for part in clip_polyline(a, lim):
+            if poly_len(part) < 2:
+                continue
+            roads.append([cls, oneway, lanes] + flat(part))
+            counts[cls] = counts.get(cls, 0) + 1
+    print(f"  roads: {len(roads)} polylines, by class {dict(sorted(counts.items()))}")
+    return {"roads": roads}
+
+
+# ---------------------------------------------------------------- aeroway
+def build_aeroway(frame, data):
+    lim = frame.half + 200
+    runways, taxiways, aprons, terminals, gates, parking = [], [], [], [], [], []
+    apron_names = []
+    for el in data["elements"]:
+        tags = el.get("tags", {})
+        aw = tags.get("aeroway")
+        if el["type"] == "node":
+            x, y = frame.xy(el["lon"], el["lat"])
+            if abs(x) > lim or abs(y) > lim:
+                continue
+            if aw == "gate":
+                gates.append([r1(x), r1(y), tags.get("ref", tags.get("name", ""))])
+            elif aw == "parking_position":
+                parking.append([r1(x), r1(y), tags.get("ref", tags.get("name", ""))])
+            continue
+        if aw == "runway" and el["type"] == "way" and el.get("geometry"):
+            a = frame.geom_xy(el["geometry"])
+            closed = len(a) > 3 and np.allclose(a[0], a[-1], atol=1e-3)
+            try:
+                w = float(str(tags.get("width", "")).replace("m", "").strip())
+            except ValueError:
+                w = None
+            if closed or tags.get("area") == "yes":
+                # area runway: use its long axis (PCA) as centreline, width = short extent
+                c = a.mean(0)
+                u, s, vt = np.linalg.svd(a - c, full_matrices=False)
+                ax = vt[0]
+                t = (a - c) @ ax
+                n = (a - c) @ vt[1]
+                p1, p2 = c + ax * t.min(), c + ax * t.max()
+                w = w or float(n.max() - n.min())
+            else:
+                p1, p2 = a[0], a[-1]
+            runways.append([r1(w or 45.0), tags.get("ref", ""), r1(p1[0]), r1(p1[1]), r1(p2[0]), r1(p2[1])])
+        elif aw == "taxiway" and el["type"] == "way" and el.get("geometry"):
+            a = frame.geom_xy(el["geometry"])
+            if tags.get("area") == "yes":
+                continue
+            for part in clip_polyline(a, lim):
+                taxiways.append(flat(part))
+        elif aw == "apron":
+            for ring in outer_rings(el, frame):
+                c = ring.mean(0)
+                if abs(c[0]) > lim or abs(c[1]) > lim:
+                    continue
+                aprons.append(flat(dp_ring(ring, 0.5)))
+                apron_names.append(tags.get("name", ""))
+        elif aw == "terminal":
+            h, _ = tag_height(tags)
+            for ring in outer_rings(el, frame):
+                c = ring.mean(0)
+                if abs(c[0]) > lim or abs(c[1]) > lim:
+                    continue
+                terminals.append([r1(h)] + flat(dp_ring(ring, 0.5)))
+    # OSM often splits one runway into several ways (displaced thresholds, blast pads):
+    # merge segments sharing a ref into one centreline spanning their extreme endpoints.
+    merged, groups = [], {}
+    for rw in runways:
+        if rw[1]:
+            groups.setdefault(rw[1], []).append(rw)
+        else:
+            merged.append(rw)
+    for ref, segs in groups.items():
+        pts = np.array([[s[2], s[3]] for s in segs] + [[s[4], s[5]] for s in segs])
+        main = max(segs, key=lambda s: math.hypot(s[4] - s[2], s[5] - s[3]))
+        ax = np.array([main[4] - main[2], main[5] - main[3]])
+        ax /= np.linalg.norm(ax)
+        t = (pts - pts[0]) @ ax
+        p1, p2 = pts[int(np.argmin(t))], pts[int(np.argmax(t))]
+        merged.append([main[0], ref, r1(p1[0]), r1(p1[1]), r1(p2[0]), r1(p2[1])])
+    if len(merged) != len(runways):
+        print(f"  runways: merged {len(runways)} OSM segments into {len(merged)}")
+    runways = merged
+    out = {"runways": runways, "taxiways": taxiways, "aprons": aprons, "apronNames": apron_names,
+           "terminals": terminals, "gates": gates, "parking": parking}
+    print("  aeroway: " + ", ".join(f"{k}={len(v)}" for k, v in out.items()))
+    return out
+
+
+# ---------------------------------------------------------------- tiles / imagery
+def merc_px(lon, lat, z, ts=256):
+    n = 2 ** z
+    x = (lon + 180.0) / 360.0 * n * ts
+    lat_r = np.radians(lat)
+    y = (1.0 - np.log(np.tan(lat_r) + 1.0 / np.cos(lat_r)) / math.pi) / 2.0 * n * ts
+    return x, y
+
+
+def fetch_tiles(url_fmt, tiles, subdir, ext, workers=8):
+    d = os.path.join(CACHE, subdir)
+    os.makedirs(d, exist_ok=True)
+    sess = requests.Session()
+    sess.headers.update(UA)
+    fails = []
+
+    def get(t):
+        z, x, y = t
+        p = os.path.join(d, f"{z}_{x}_{y}.{ext}")
+        if os.path.exists(p) and os.path.getsize(p) > 0:
+            return p
+        for i in range(4):
+            try:
+                r = sess.get(url_fmt.format(z=z, x=x, y=y), timeout=60)
+                if r.status_code == 200 and len(r.content) > 100:
+                    with open(p + ".tmp", "wb") as f:
+                        f.write(r.content)
+                    os.replace(p + ".tmp", p)
+                    return p
+                if r.status_code == 404:
+                    break
+            except Exception:
+                pass
+            time.sleep(1.5 * (i + 1))
+        fails.append(t)
+        return None
+
+    with ThreadPoolExecutor(workers) as ex:
+        res = list(ex.map(get, tiles))
+    return dict(zip(tiles, res)), fails
+
+
+def mosaic(frame, z, url_fmt, subdir, ext, mode, pad_m=300.0):
+    s, w, n, e = frame.bbox(pad_m)
+    x0, y1 = merc_px(w, s, z)
+    x1, y0 = merc_px(e, n, z)
+    tx0, tx1 = int(x0 // 256), int(x1 // 256)
+    ty0, ty1 = int(y0 // 256), int(y1 // 256)
+    tiles = [(z, x, y) for y in range(ty0, ty1 + 1) for x in range(tx0, tx1 + 1)]
+    print(f"  {subdir} z{z}: {tx1-tx0+1}x{ty1-ty0+1} = {len(tiles)} tiles", flush=True)
+    paths, fails = fetch_tiles(url_fmt, tiles, subdir, ext)
+    if fails:
+        print(f"  WARNING: {len(fails)} tiles failed: {fails[:10]}")
+    W, H = (tx1 - tx0 + 1) * 256, (ty1 - ty0 + 1) * 256
+    nb = 3 if mode == "RGB" else 3
+    mos = np.zeros((H, W, nb), np.uint8)
+    for (zz, x, y), p in paths.items():
+        if p is None:
+            continue
+        im = Image.open(p).convert("RGB")
+        if im.size != (256, 256):
+            im = im.resize((256, 256))
+        mos[(y - ty0) * 256:(y - ty0 + 1) * 256, (x - tx0) * 256:(x - tx0 + 1) * 256] = np.asarray(im)
+    return mos, tx0 * 256, ty0 * 256, len(fails)
+
+
+def bilinear(img, px, py):
+    """img HxWxC (float or uint8), px/py float arrays in pixel coords (pixel centres at i+0.5)."""
+    H, W = img.shape[:2]
+    fx = np.clip(px - 0.5, 0, W - 1.000001)
+    fy = np.clip(py - 0.5, 0, H - 1.000001)
+    x0 = np.floor(fx).astype(np.int64)
+    y0 = np.floor(fy).astype(np.int64)
+    ax = (fx - x0)[..., None]
+    ay = (fy - y0)[..., None]
+    im = img if img.ndim == 3 else img[..., None]
+    a = im[y0, x0].astype(np.float32)
+    b = im[y0, x0 + 1].astype(np.float32)
+    c = im[y0 + 1, x0].astype(np.float32)
+    d = im[y0 + 1, x0 + 1].astype(np.float32)
+    out = (a * (1 - ax) + b * ax) * (1 - ay) + (c * (1 - ax) + d * ax) * ay
+    return out if img.ndim == 3 else out[..., 0]
+
+
+def reproject(frame, img, ox, oy, z, N, rows_per=256):
+    """Sample a Mercator mosaic (origin global px ox,oy at zoom z) onto the local NxN square."""
+    h = frame.half
+    out = np.zeros((N, N) + img.shape[2:], np.float32)
+    xs = -h + (np.arange(N) + 0.5) * (2 * h / N)
+    for r0 in range(0, N, rows_per):
+        r = np.arange(r0, min(N, r0 + rows_per))
+        ys = h - (r + 0.5) * (2 * h / N)
+        X, Y = np.meshgrid(xs, ys)
+        lon, lat = frame.ll(X, Y)
+        mx, my = merc_px(lon, lat, z)
+        out[r0:r0 + len(r)] = bilinear(img, mx - ox, my - oy)
+    return out
+
+
+ESRI = "https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}"
+
+
+EOX_S2 = "https://tiles.maps.eox.at/wmts/1.0.0/s2cloudless-2020_3857/default/g/{z}/{y}/{x}.jpg"
+
+
+def build_ground(frame, z, url=ESRI, sub="esri", name="ground"):
+    mos, ox, oy, nf = mosaic(frame, z, url, sub, "jpg", "RGB")
+    out = reproject(frame, mos, ox, oy, z, 4096)
+    im = Image.fromarray(np.clip(out + 0.5, 0, 255).astype(np.uint8))
+    p = os.path.join(frame.out, f"{name}.jpg")
+    im.save(p, quality=90, optimize=True)
+    print(f"  wrote {p} ({os.path.getsize(p)/1e6:.2f} MB)")
+    im2 = im.resize((2048, 2048), Image.LANCZOS)
+    p2 = os.path.join(frame.out, f"{name}_2k.jpg")
+    im2.save(p2, quality=88, optimize=True)
+    print(f"  wrote {p2} ({os.path.getsize(p2)/1e6:.2f} MB)")
+    return nf
+
+
+# ---------------------------------------------------------------- check overlay
+def to_px(frame, a, N):
+    a = np.asarray(a, dtype=np.float64).reshape(-1, 2)
+    return [((x + frame.half) / (2 * frame.half) * N, (frame.half - y) / (2 * frame.half) * N) for x, y in a]
+
+
+def check_canvas(frame, dark=0.45):
+    from PIL import ImageEnhance
+    im = Image.open(os.path.join(frame.out, "ground_2k.jpg")).convert("RGB")
+    im = ImageEnhance.Brightness(im).enhance(dark)
+    return im

intro-sequence/tools/export-cues.mjs

@@ -0,0 +1,40 @@
+// Export the film clock for the score: every visual event the audio locks to.
+import fs from 'node:fs';
+import { T, FEEDS, CITIES, DURATION, captureTimes, CAPTURE_SLOW } from '../src/timeline.js';
+import { angDist } from '../src/geo.js';
+
+const heroes = JSON.parse(fs.readFileSync('imagery/hero/index.json', 'utf8'));
+const caps = captureTimes(heroes.length).map((t, i) => ({ t, slow: i < CAPTURE_SLOW, lon: heroes[i].lon }));
+
+// tile reveal times — same formula as the globe shader and HUD
+const f = (v) => v - Math.floor(v);
+const hash3 = (x, y, z) => {
+  const px = f(x * 0.3183099 + 0.71) * 17, py = f(y * 0.3183099 + 0.113) * 17, pz = f(z * 0.3183099 + 0.419) * 17;
+  return f(px * py * pz * (px + py + pz));
+};
+const tiles = [];
+[[3, T.zWave[0], 0.35], [4, T.zWave[1], 0.3], [5, T.zWave[2], 0.25]].forEach(([z, wave, jit]) => {
+  const n = 2 ** z;
+  for (let x = 0; x < n; x++)
+    for (let y = 0; y < n; y++) {
+      const lon = ((x + 0.5) / n) * 360 - 180;
+      const lat = (Math.atan(Math.sinh(Math.PI * (1 - 2 * ((y + 0.5) / n)))) * 180) / Math.PI;
+      // only the hemisphere facing the camera is heard
+      const d = angDist(0, 0, lon, lat);
+      tiles.push({ t: wave + (d / Math.PI) * 2.6 + hash3(x, y, z) * jit, z, pan: Math.max(-1, Math.min(1, lon / 90)), vis: angDist(10, 8, lon, lat) < 1.4 });
+    }
+});
+
+// boot console keystrokes
+const boot = [];
+[['GEV://OBSERVER-1  rev 0.2.1', T.boot, 55], ['allocating substrate ........ 1.0000  OK', T.boot + 0.75, 55], ['loading priors .............. NONE', T.boot + 1.35, 55], ['> seed --origin 0.0000°N 0.0000°E', T.boot + 2.1, 26]].forEach(([s, st, cps], line) => {
+  for (let i = 0; i < s.length; i++) {
+    const t = st + i / cps;
+    if (t < T.collapse) boot.push({ t, ch: s[i], line });
+  }
+});
+
+const status = [77.4, 78.5, 79.6, 80.7, 81.7];
+const rapid = Array.from({ length: 7 }, (_, i) => T.rapid + i * 0.22);
+fs.writeFileSync('audio/cues.json', JSON.stringify({ T, DURATION, feeds: FEEDS.map((x) => ({ key: x.key, t: x.t })), cities: CITIES.map((c) => ({ slug: c.slug, t0: c.t0, t1: c.t1 })), caps, tiles, boot, status, rapid }, null, 1));
+console.log('cues:', caps.length, 'captures,', tiles.length, 'tiles,', boot.length, 'keystrokes');

intro-sequence/tools/fetch/cctv_count.py

@@ -0,0 +1,511 @@
+#!/usr/bin/env python3
+"""Count distinct cameras in every keyless CCTV catalog the app supports.
+
+Fetches each source's FULL public catalog (no anchor selection, no
+DEFAULT_*_MAX_SOURCES caps) and counts distinct cameras two ways:
+  raw   - distinct camera ids listed in the catalog at all
+  valid - distinct ids passing the app's own validity filters (in service /
+          online / official still or stream URL / plausible coordinates),
+          i.e. what server/providers/cctv/* would accept before capping.
+The headline number written to data/extra_counts.json is the conservative
+`valid` count. Sources that fail are skipped, never estimated.
+
+Usage: python3 -I cctv_count.py <out_json> [<detail_json>]
+"""
+import json, math, re, sys, time
+from concurrent.futures import ThreadPoolExecutor
+from urllib.parse import urlparse, parse_qs
+import requests
+
+UA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36'
+REPO = '/home/user/gods-eye-view'
+
+
+def sess():
+    s = requests.Session()
+    s.headers.update({'User-Agent': UA, 'Digitraffic-User': 'gods-eye-view'})
+    return s
+
+
+def get(url, timeout=60, **kw):
+    r = sess().get(url, timeout=timeout, **kw)
+    r.raise_for_status()
+    return r
+
+
+def fnum(v):
+    try:
+        f = float(v)
+        return f if math.isfinite(f) else None
+    except (TypeError, ValueError):
+        return None
+
+
+def inbox(lat, lon, la0, la1, lo0, lo1):
+    return lat is not None and lon is not None and la0 <= lat <= la1 and lo0 <= lon <= lo1
+
+
+SRC = {}
+
+
+def source(label, country):
+    def deco(fn):
+        SRC[label] = (fn, country)
+        return fn
+    return deco
+
+
+@source('TfL JamCams', 'United Kingdom')
+def tfl():
+    d = get('https://api.tfl.gov.uk/Place/Type/JamCam').json()
+    raw, ok = set(), set()
+    for p in d:
+        raw.add(p['id'])
+        props = {a['key']: a['value'] for a in p.get('additionalProperties', [])}
+        if str(props.get('available')).lower() != 'true':
+            continue
+        if not (props.get('imageUrl') or '').startswith('https://s3-eu-west-1.amazonaws.com/jamcams.tfl.gov.uk/'):
+            continue
+        if fnum(p.get('lat')) is None or fnum(p.get('lon')) is None:
+            continue
+        ok.add(p['id'])
+    return raw, ok, 'one Place per camera; available=true + official S3 still'
+
+
+@source('NYC DOT', 'United States')
+def nyc():
+    d = get('https://webcams.nyctmc.org/api/cameras').json()
+    raw = {c['id'] for c in d}
+    ok = {c['id'] for c in d if str(c.get('isOnline')).strip().lower() == 'true'
+          and inbox(fnum(c.get('latitude')), fnum(c.get('longitude')), 40.4, 41.0, -74.3, -73.6)}
+    return raw, ok, 'one row per camera; isOnline=true'
+
+
+@source('Caltrans', 'United States')
+def caltrans():
+    raw, ok = set(), set()
+    notes = []
+
+    def one(dist):
+        err = None
+        for attempt in range(5):  # cwwp2 resets connections under parallel load
+            try:
+                return dist, get(f'https://cwwp2.dot.ca.gov/data/d{dist}/cctv/cctvStatusD{dist:02d}.json').json()
+            except Exception as e:
+                err = e
+                time.sleep(1 + attempt)
+        return dist, err
+    with ThreadPoolExecutor(3) as ex:
+        res = list(ex.map(one, range(1, 13)))
+    for dist, d in res:
+        if isinstance(d, Exception):
+            notes.append(f'D{dist} failed: {str(d)[:60]}')
+            continue
+        for i, row in enumerate(d.get('data', [])):
+            c = row.get('cctv') or {}
+            loc = c.get('location') or {}
+            name = (loc.get('locationName') or '').strip()
+            m = re.match(r'^([A-Za-z0-9_-]+)\s*--', name)
+            key = f"d{dist}-{(m.group(1) if m else c.get('index') or name or i)}".lower()
+            raw.add(key)
+            if str(c.get('inService')).lower() != 'true':
+                continue
+            if fnum(loc.get('latitude')) is None or fnum(loc.get('longitude')) is None:
+                continue
+            url = ((c.get('imageData') or {}).get('static') or {}).get('currentImageURL') or ''
+            if not url.startswith('https://cwwp2.dot.ca.gov/'):
+                continue
+            ok.add(key)
+    return raw, ok, 'all 12 districts; inService=true + cwwp2 still. ' + '; '.join(notes)
+
+
+@source('WSDOT', 'United States')
+def wsdot():
+    d = json.loads(get('https://data.wsdot.wa.gov/travelcenter/Cameras.json').content.decode('cp1252'))
+    raw, ok = set(), set()
+    for f in d['features']:
+        a = f.get('attributes') or {}
+        cid = a.get('CameraID')
+        if not isinstance(cid, int) or cid <= 0:
+            continue
+        raw.add(cid)
+        if (a.get('ImageURL') or '').strip().startswith('https://images.wsdot.wa.gov/') and fnum((f.get('geometry') or {}).get('x')) is not None:
+            ok.add(cid)
+    return raw, ok, 'one feature per CameraID; official images.wsdot.wa.gov still'
+
+
+@source('King County DOT', 'United States')
+def kingco():
+    d = get('https://services.arcgis.com/Ej0PsM5Aw677QF1W/arcgis/rest/services/TRAFFICCAMERA_POINT_2029/FeatureServer/0/query?where=1%3D1&outFields=AssetID,Location,ImageURL,Live,Model,Manufacturer,Owner,CurrentStatus&f=geojson').json()
+    raw, ok = set(), set()
+    for f in d['features']:
+        p = f.get('properties') or {}
+        aid = p.get('AssetID')
+        if not isinstance(aid, int) or aid <= 0:
+            continue
+        raw.add(aid)
+        if p.get('Live') != 1 or str(p.get('CurrentStatus') or '').strip() != 'Active':
+            continue
+        if str(p.get('Owner') or '').strip() == 'WSDOT':
+            continue  # WSDOT-owned rows are WSDOT cameras (counted under WSDOT)
+        url = (p.get('ImageURL') or '').strip().replace('http://info.kingcounty.gov/', 'https://info.kingcounty.gov/')
+        if not url.startswith('https://info.kingcounty.gov/'):
+            continue
+        ok.add(aid)
+    note = 'Live=1 + Active, WSDOT-owned rows excluded (avoid double count)'
+    if d.get('exceededTransferLimit') or (d.get('properties') or {}).get('exceededTransferLimit'):
+        note += ' WARNING: transfer limit exceeded'
+    return raw, ok, note
+
+
+@source('DriveBC', 'Canada')
+def drivebc():
+    d = get('https://www.drivebc.ca/api/webcams/').json()
+    raw, ok = set(), set()
+    for c in d:
+        cid = c.get('id')
+        if not isinstance(cid, int) or cid <= 0:
+            continue
+        raw.add(cid)
+        if c.get('is_on') is not True or c.get('should_appear') is not True:
+            continue
+        coords = (c.get('location') or {}).get('coordinates') or [None, None]
+        if not inbox(fnum(coords[1]), fnum(coords[0]), 48.0, 60.5, -139.5, -113.5):
+            continue
+        ok.add(cid)
+    return raw, ok, 'one webcam per id; is_on + should_appear'
+
+
+@source('Fintraffic Digitraffic', 'Finland')
+def fintraffic():
+    d = get('https://tie.digitraffic.fi/api/weathercam/v1/stations', headers={'Accept-Encoding': 'gzip'}).json()
+    raw, ok, presets = set(), set(), 0
+    for f in d['features']:
+        p = f.get('properties') or {}
+        sid = str(p.get('id') or '')
+        if not sid:
+            continue
+        raw.add(sid)
+        if str(p.get('collectionStatus') or '').upper() != 'GATHERING':
+            continue
+        live = [pr for pr in p.get('presets') or [] if pr.get('inCollection') is True and re.fullmatch(r'C\d{7}', str(pr.get('id'))) and str(pr['id']).startswith(sid)]
+        if live:
+            ok.add(sid)
+            presets += len(live)
+    return raw, ok, f'counted per STATION (camera site), not per preset view; {presets} live presets (the app treats each preset as a camera)'
+
+
+@source('Statens vegvesen', 'Norway')
+def vegvesen():
+    d = get('https://ogckart-sn1.atlas.vegvesen.no/ogc/features/v1/collections/datex_3_1:CctvSimple/items?f=application/geo%2Bjson&limit=5000',
+            headers={'Accept': 'application/geo+json,application/json'}).json()
+    raw, ok = set(), set()
+    for f in d['features']:
+        p = f.get('properties') or {}
+        rid = str(p.get('cameraId') or '').strip()
+        if not re.fullmatch(r'[A-Za-z0-9_-]{1,40}', rid):
+            continue
+        raw.add(rid)
+        av = str(p.get('status.stillImageAvailability') or '').strip()
+        if av and av != 'videoOrImagesAvailable':
+            continue
+        if (p.get('stillImageUrl') or '') != f'https://kamera.atlas.vegvesen.no/api/images/{rid}':
+            continue
+        c = (f.get('geometry') or {}).get('coordinates') or [None, None]
+        if not inbox(fnum(c[1]), fnum(c[0]), 57.5, 71.5, 4.0, 31.5):
+            continue
+        ok.add(rid)
+    note = f"numberMatched={d.get('numberMatched')} numberReturned={d.get('numberReturned')}"
+    return raw, ok, 'stillImageAvailability ok + official still; ' + note
+
+
+@source('City of Tallinn', 'Estonia')
+def tallinn():
+    d = json.load(open(f'{REPO}/config/cctv_sources.tallinn.json'))
+    raw, ok = set(), set()
+    for c in d:
+        cid = str(c.get('id') or '').strip()
+        if not cid:
+            continue
+        raw.add(cid)
+        url = c.get('snapshotUrl') or c.get('url') or ''
+        if inbox(fnum(c.get('lat')), fnum(c.get('lon')), 59.2, 59.7, 24.3, 25.4) and url.startswith('https://ristmikud.tallinn.ee/'):
+            ok.add(url)
+    return raw, ok, 'curated repo catalog (config/cctv_sources.tallinn.json) of ristmikud.tallinn.ee stills; distinct frame URLs'
+
+
+@source('Transpordiamet Tarktee', 'Estonia')
+def tarktee():
+    lx = get('https://tarktee.transpordiamet.ee/api/v1/datex/roadCameraLocations', headers={'Accept': 'application/xml'}).text
+    ix = get('https://tarktee.transpordiamet.ee/api/v1/datex/roadCameraImages', headers={'Accept': 'application/xml'}).text
+    locs = {}
+    for m in re.finditer(r'<predefinedLocation\s+id="([^"]+)"[^>]*>([\s\S]*?)</predefinedLocation>', lx):
+        la = re.search(r'<latitude>\s*(-?\d+(?:\.\d+)?)\s*</latitude>', m.group(2), re.I)
+        lo = re.search(r'<longitude>\s*(-?\d+(?:\.\d+)?)\s*</longitude>', m.group(2), re.I)
+        if la and lo:
+            locs[m.group(1)] = (float(la.group(1)), float(lo.group(1)))
+    imgs = {}
+    for m in re.finditer(r'<trafficView\b[^>]*>([\s\S]*?)</trafficView>', ix):
+        r = re.search(r'<linearPredefinedLocationReference\b[^>]*\bid="([^"]+)"', m.group(1), re.I)
+        u = re.search(r'<urlLinkAddress>\s*([^<\s]+)\s*</urlLinkAddress>', m.group(1), re.I)
+        if r and u:
+            imgs[r.group(1)] = u.group(1)
+    raw = set(locs) | set(imgs)
+    ok = set()
+    for lid, (lat, lon) in locs.items():
+        u = imgs.get(lid, '')
+        if not u.startswith('https://tarktee.transpordiamet.ee/images/'):
+            continue
+        if not inbox(lat, lon, 57.4, 59.9, 21.5, 28.4):
+            continue
+        n = re.search(r'/images/(\d+)/', u)
+        ok.add(n.group(1) if n else lid)
+    return raw, ok, 'DATEX location joined to image; distinct camera numbers'
+
+
+@source('Via Lietuva eismoinfo', 'Lithuania')
+def lithuania():
+    rows = get('https://eismoinfo.lt/eismoinfo-backend/camera-info-table', headers={'Accept': 'application/json'}).json()
+    layers = get('https://eismoinfo.lt/eismoinfo-backend/layer-static-features/VKR', headers={'Accept': 'application/json'}).json()
+    feats = {}
+    for L in layers:
+        if L.get('layer') == 'VKR':
+            feats = {str(f.get('id')): f for f in L.get('features') or [] if f}
+    raw, ok = set(), set()
+    for r in rows:
+        rid = str(r.get('id') or '')
+        if not re.fullmatch(r'[1-9]\d{0,8}', rid):
+            continue
+        raw.add(rid)
+        f = feats.get(rid)
+        try:
+            lat, lon = f['points'][0]['point']
+        except Exception:
+            continue
+        if not inbox(fnum(lat), fnum(lon), 53.8, 56.5, 20.8, 26.9):
+            continue
+        u = urlparse(str(r.get('image') or ''))
+        if f'{u.scheme}://{u.netloc}' != 'https://eismoinfo.lt' or u.path != '/eismoinfo-backend/image-provider/camera/last' or parse_qs(u.query).get('id', [''])[0] != rid:
+            continue
+        ok.add(rid)
+    return raw, ok, 'camera table joined to VKR layer; official still endpoint'
+
+
+@source('Live Traffic NSW', 'Australia')
+def nsw():
+    d = get('https://data.livetraffic.com/cameras/traffic-cam.json').json()
+    raw, ok = set(), set()
+    for f in d['features']:
+        p = f.get('properties') or {}
+        fid = str(f.get('id') or p.get('id') or p.get('title') or '').strip()
+        if not fid:
+            continue
+        raw.add(fid)
+        href = (p.get('href') or '').replace('http://', 'https://')
+        c = (f.get('geometry') or {}).get('coordinates') or [None, None]
+        if href.startswith('https://webcams.transport.nsw.gov.au/') and inbox(fnum(c[1]), fnum(c[0]), -38.0, -28.0, 140.0, 154.5):
+            ok.add(fid)
+    return raw, ok, 'one feature per camera; official webcams.transport.nsw.gov.au still'
+
+
+@source('City of Calgary', 'Canada')
+def calgary():
+    d = get('https://data.calgary.ca/resource/k7p9-kppz.json?$limit=5000').json()
+    raw, ok = set(), set()
+    for c in d:
+        url = ((c.get('camera_url') or {}).get('url') or '').strip()
+        if not url:
+            continue
+        u = re.sub(r'^http://', 'https://', url)
+        m = re.search(r'loc(\d+)\.jpg$', urlparse(u).path, re.I)
+        key = m.group(1) if m else urlparse(u).path
+        raw.add(key)
+        coords = (c.get('point') or {}).get('coordinates') or [None, None]
+        if u.startswith('https://trafficcam.calgary.ca/') and inbox(fnum(coords[1]), fnum(coords[0]), 50.7, 51.4, -114.5, -113.7):
+            ok.add(key)
+    return raw, ok, f'{len(d)} rows ($limit=5000); distinct trafficcam.calgary.ca image ids'
+
+
+@source('City of Toronto RESCU', 'Canada')
+def toronto():
+    t = get('https://opendata.toronto.ca/transportation/tmc/rescucameraimages/Data/tmcearthcameras.json').text
+    d = json.loads(t[t.index('(') + 1: t.rindex(')')])
+    raw, ok = set(), set()
+    for c in d['Data']:
+        n = str(c.get('Number') or '').strip()
+        if not n:
+            continue
+        raw.add(n)
+        if re.fullmatch(r'\d{1,6}', n) and inbox(fnum(c.get('Latitude')), fnum(c.get('Longitude')), 43.4, 44.0, -79.8, -79.0):
+            ok.add(n)
+    return raw, ok, 'one row per numbered RESCU camera'
+
+
+@source('Servei Català de Trànsit', 'Spain')
+def catalonia():
+    x = get('https://www.gencat.cat/transit/opendata/cameres.xml').text
+    hosts = {'mct.gencat.cat': '/mct2bo/', 'www.bcn.cat': '/transit/imatges/', 'emap.terrassa.cat': '/it_terrassa/'}
+    raw, ok = set(), set()
+    for m in re.finditer(r'<gml:featureMember>([\s\S]*?)</gml:featureMember>', x):
+        b = m.group(1)
+        co = re.search(r'<gml:coordinates[^>]*>([^<]+)</gml:coordinates>', b)
+        lk = re.search(r'<cite:link>([^<]*)</cite:link>', b)
+        if not co or not lk:
+            continue
+        link = lk.group(1).replace('&amp;', '&').strip()
+        u = urlparse(link)
+        cam = parse_qs(u.query).get('sctidcam', [''])[0]
+        key = f'sct:{cam}' if u.hostname == 'mct.gencat.cat' and cam else f'{u.hostname}{u.path}'
+        raw.add(key)
+        lon, lat = (fnum(v) for v in co.group(1).split(',')[:2])
+        if not inbox(lat, lon, 40.4, 42.95, 0.1, 3.4):
+            continue
+        d = hosts.get(u.hostname or '')
+        if not d or not u.path.startswith(d) or u.username or u.password or u.port:
+            continue
+        f = u.path[len(d):]
+        if not f or '/' in f:
+            continue
+        if u.hostname == 'mct.gencat.cat' and (f != 'RenderService' or not re.fullmatch(r'[a-z0-9]+\.(gif|jpe?g)', cam, re.I)):
+            continue
+        ok.add(key)
+    return raw, ok, 'SCT + Barcelona IMI + Terrassa; keyed by frame file (feed fid is unstable)'
+
+
+@source('City of Austin', 'United States')
+def austin():
+    d = get('https://data.austintexas.gov/api/views/b4k4-adkb/rows.json?accessType=DOWNLOAD').json()
+    cols = [c['fieldName'] for c in d['meta']['view']['columns']]
+    raw, ok = set(), set()
+    for row in d['data']:
+        r = dict(zip(cols, row))
+        cid = str(r.get('camera_id') or '').strip()
+        if not cid:
+            continue
+        raw.add(cid)
+        st = (r.get('camera_status') or '').strip().upper()
+        if st and st != 'TURNED_ON':
+            continue
+        m = re.match(r'POINT \(([-\d.]+) ([-\d.]+)\)', r.get('location') or '')
+        if not m or not inbox(fnum(m.group(2)), fnum(m.group(1)), 29.9, 30.8, -98.2, -97.3):
+            continue
+        ok.add(cid)
+    return raw, ok, 'camera_status TURNED_ON'
+
+
+TXDOT = 'ABL AMA ATL AUS BMT BWD BRY CHS CRP DAL ELP FTW HOU LRD LBB LFK ODA PAR PHR SJT SAT TYL WAC WFS YKM'.split()
+
+
+@source('TxDOT ITS', 'United States')
+def txdot():
+    def one(code):
+        for attempt in range(2):
+            try:
+                return code, get(f'https://its.txdot.gov/its/DistrictIts/GetCctvStatusListByDistrict?districtCode={code}',
+                                 headers={'Accept': 'application/json'}, timeout=60).json()
+            except Exception as e:
+                err = e
+        return code, err
+    with ThreadPoolExecutor(8) as ex:
+        res = list(ex.map(one, TXDOT))
+    raw, ok, notes, per = set(), set(), [], {}
+    for code, d in res:
+        if isinstance(d, Exception):
+            notes.append(f'{code} failed: {str(d)[:50]}')
+            continue
+        n = 0
+        for rows in (d.get('roadwayCctvStatuses') or {}).values():
+            for r in rows or []:
+                icd = str(r.get('icd_Id') or '').strip()
+                if not icd:
+                    continue
+                raw.add(icd)
+                if r.get('statusDescription') != 'Device Online' or r.get('hasSnapshot') is False:
+                    continue
+                lat, lon = r.get('latitude'), r.get('longitude')
+                if not (isinstance(lat, (int, float)) and isinstance(lon, (int, float)) and inbox(lat, lon, 25.5, 36.7, -106.8, -93.3)):
+                    continue
+                if icd not in ok:
+                    n += 1
+                ok.add(icd)
+        per[code] = n
+    return raw, ok, f'all 25 districts; Device Online + snapshot; per-district {per}. ' + '; '.join(notes)
+
+
+@source('Ontario 511', 'Canada')
+def ontario():
+    d = get('https://511on.ca/api/v2/get/cameras?format=json&lang=en', headers={'Accept': 'application/json'}).json()
+    raw, ok, views = set(), set(), 0
+    for r in d:
+        rid = str(r.get('Id') or r.get('id') or '').strip()
+        if not rid:
+            continue
+        raw.add(rid)
+        if not inbox(fnum(r.get('Latitude')), fnum(r.get('Longitude')), 41.0, 57.5, -95.6, -74.0):
+            continue
+        good = []
+        for v in r.get('Views') or r.get('views') or []:
+            if str(v.get('Status') or '').strip().lower() != 'enabled':
+                continue
+            u = urlparse(str(v.get('Url') or '').strip())
+            if u.scheme == 'https' and (u.hostname == '511on.ca' or (u.hostname or '').endswith('.traveliq.co')) and re.fullmatch(r'/map/Cctv/[A-Za-z0-9_.-]+', u.path):
+                good.append(v)
+        if good:
+            ok.add(rid)
+            views += len(good)
+    return raw, ok, f'counted per camera row, not per view; {views} enabled views'
+
+
+@source('DelDOT', 'United States')
+def deldot():
+    d = get('https://tmc.deldot.gov/json/videocamera.json', headers={'Accept': 'application/json'}).json()
+    raw, ok = set(), set()
+    for r in d.get('videoCameras') or []:
+        cid = str(r.get('id') or '').strip()
+        if not cid:
+            continue
+        raw.add(cid)
+        if str(r.get('status')).lower() != 'active':
+            continue
+        if not inbox(fnum(r.get('lat')), fnum(r.get('lon')), 38.4, 39.9, -75.85, -75.0):
+            continue
+        u = urlparse(str((r.get('urls') or {}).get('m3u8s') or ''))
+        if u.scheme != 'https' or u.hostname != 'video.deldot.gov' or u.port not in (None, 443) or u.username or not re.fullmatch(r'/live/[A-Za-z0-9_.-]+/playlist\.m3u8', u.path):
+            continue
+        if not re.fullmatch(r'[A-Za-z0-9_-]{1,80}', cid):
+            continue
+        ok.add(cid)
+    return raw, ok, 'status active + official HLS stream'
+
+
+def run(label):
+    fn, country = SRC[label]
+    t0 = time.time()
+    try:
+        raw, ok, note = fn()
+        if not ok:
+            raise RuntimeError('catalog parsed to zero cameras')
+        return label, dict(country=country, raw=len(raw), valid=len(ok), note=note, secs=round(time.time() - t0, 1))
+    except Exception as e:
+        return label, dict(country=country, error=f'{type(e).__name__}: {str(e)[:200]}', secs=round(time.time() - t0, 1))
+
+
+if __name__ == '__main__':
+    out = sys.argv[1]
+    detail = sys.argv[2] if len(sys.argv) > 2 else None
+    with ThreadPoolExecutor(8) as ex:
+        results = dict(ex.map(run, list(SRC)))
+    counted = {k: v for k, v in results.items() if 'valid' in v}
+    for k, v in results.items():
+        print(f"{k:28s} {v.get('country', ''):15s} raw={v.get('raw', '-'):>6} valid={v.get('valid', '-'):>6}  {v.get('error') or v.get('note')}")
+    total = sum(v['valid'] for v in counted.values())
+    res = {
+        'cctv_catalog': total,
+        'cctv_sources': {k: v['valid'] for k, v in counted.items()},
+        'cctv_countries': len({v['country'] for v in counted.values()}),
+        'fetched_utc': time.strftime('%Y-%m-%dT%H:%M:%SZ', time.gmtime()),
+    }
+    print('TOTAL valid', total, 'raw', sum(v['raw'] for v in counted.values()), 'countries', res['cctv_countries'])
+    json.dump(res, open(out, 'w'), ensure_ascii=False, indent=2)
+    if detail:
+        json.dump(results, open(detail, 'w'), ensure_ascii=False, indent=2)

intro-sequence/tools/fetch/cctv_fetch.py

@@ -0,0 +1,406 @@
+#!/usr/bin/env python3
+"""Download real current still frames from keyless public traffic-camera feeds.
+
+Stage 1 (this script): build candidate lists from each source's public catalog
+(endpoints mirror server/providers/cctv/*), sample a spread of cameras, download
+frames, compute quality metrics, write <work>/frames/*.jpg + <work>/candidates.json.
+Stage 2 (cctv_select.py) filters, crops to 640x360 and writes cctv/index.json.
+
+Usage: python3 -I cctv_fetch.py <work_dir>
+"""
+import base64, hashlib, io, json, math, random, re, sys, time
+import xml.etree.ElementTree as ET
+from concurrent.futures import ThreadPoolExecutor
+import requests
+from PIL import Image, ImageStat, ImageFilter
+
+WORK = sys.argv[1]
+import os
+os.makedirs(f'{WORK}/frames', exist_ok=True)
+UA_BROWSER = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36'
+S = requests.Session()
+S.headers.update({'User-Agent': UA_BROWSER, 'Digitraffic-User': 'gods-eye-intro'})
+rng = random.Random(42)
+
+
+def get(url, **kw):
+    kw.setdefault('timeout', 40)
+    r = S.get(url, **kw)
+    r.raise_for_status()
+    return r
+
+
+def C(source, name, city, country, lat, lon, url, kind='image'):
+    return dict(source=source, name=name.strip(), city=city, country=country, lat=round(float(lat), 5), lon=round(float(lon), 5), url=url, kind=kind)
+
+
+def nearest(cands, anchors, n):
+    """Spread a pick across anchors: round-robin, nearest cameras to each anchor first, randomized a bit."""
+    buckets = []
+    for (alat, alon, label) in anchors:
+        b = sorted(cands, key=lambda c: (c['lat'] - alat) ** 2 + ((c['lon'] - alon) * math.cos(math.radians(alat))) ** 2)[:max(n * 3, 12)]
+        rng.shuffle(b)
+        for c in b:
+            c['city'] = label if c.get('city') in (None, '', '?') else c['city']
+        buckets.append(b)
+    out, seen = [], set()
+    while len(out) < n and any(buckets):
+        for b in buckets:
+            while b:
+                c = b.pop()
+                if c['url'] not in seen:
+                    seen.add(c['url']); out.append(c); break
+    return out[:n]
+
+
+def sample(cands, n):
+    cands = list(cands)
+    rng.shuffle(cands)
+    return cands[:n]
+
+
+SOURCES = {}
+
+
+def source(fn):
+    SOURCES[fn.__name__] = fn
+    return fn
+
+
+@source
+def tfl(n):
+    d = get('https://api.tfl.gov.uk/Place/Type/JamCam').json()
+    out = []
+    for p in d:
+        props = {a['key']: a['value'] for a in p.get('additionalProperties', [])}
+        if props.get('available') != 'true' or not props.get('imageUrl'):
+            continue
+        out.append(C('TfL JamCams', p['commonName'], 'London', 'United Kingdom', p['lat'], p['lon'], props['imageUrl']))
+    return nearest(out, [(51.5074, -0.1278, 'London')], n)
+
+
+@source
+def nyc(n):
+    d = get('https://webcams.nyctmc.org/api/cameras').json()
+    out = [C('NYC DOT', c['name'], f"New York ({c.get('area')})", 'United States', c['latitude'], c['longitude'],
+             f"https://webcams.nyctmc.org/api/cameras/{c['id']}/image") for c in d if str(c.get('isOnline')).lower() == 'true']
+    return nearest(out, [(40.758, -73.9855, 'New York'), (40.7128, -74.006, 'New York'), (40.6782, -73.9442, 'New York'), (40.7282, -73.7949, 'New York')], n)
+
+
+@source
+def caltrans(n):
+    out = []
+    for dist, city in [(4, 'San Francisco Bay Area'), (7, 'Los Angeles'), (11, 'San Diego'), (3, 'Sacramento')]:
+        try:
+            d = get(f'https://cwwp2.dot.ca.gov/data/d{dist}/cctv/cctvStatusD{dist:02d}.json').json()
+        except Exception as e:
+            print('caltrans', dist, e); continue
+        for row in d['data']:
+            c = row['cctv']
+            url = (c.get('imageData', {}).get('static') or {}).get('currentImageURL')
+            if c.get('inService') != 'true' or not url:
+                continue
+            loc = c['location']
+            out.append(C('Caltrans CCTV', loc['locationName'], loc.get('nearbyPlace') or city, 'United States', loc['latitude'], loc['longitude'], url))
+    return nearest(out, [(37.7793, -122.4193, 'San Francisco'), (34.0537, -118.2428, 'Los Angeles'), (32.7157, -117.1611, 'San Diego'), (38.5816, -121.4944, 'Sacramento')], n)
+
+
+@source
+def wsdot(n):
+    d = json.loads(get('https://data.wsdot.wa.gov/travelcenter/Cameras.json').content.decode('cp1252'))
+    out = []
+    for f in d['features']:
+        a, g = f['attributes'], f['geometry']
+        url = a.get('ImageURL') or ''
+        if not url.startswith('https://images.wsdot.wa.gov/'):
+            continue
+        lon = g['x'] / 6378137 * 180 / math.pi
+        lat = (2 * math.atan(math.exp(g['y'] / 6378137)) - math.pi / 2) * 180 / math.pi
+        out.append(C('WSDOT', a['CameraTitle'], '', 'United States', lat, lon, url))
+    return nearest(out, [(47.6062, -122.3321, 'Seattle'), (47.6588, -117.426, 'Spokane')], n)
+
+
+@source
+def kingco(n):
+    d = get('https://services.arcgis.com/Ej0PsM5Aw677QF1W/arcgis/rest/services/TRAFFICCAMERA_POINT_2029/FeatureServer/0/query?where=1%3D1&outFields=AssetID,Location,ImageURL,Live,Model,Manufacturer,Owner,CurrentStatus&f=geojson').json()
+    out = []
+    for f in d['features']:
+        p = f['properties']
+        url = (p.get('ImageURL') or '').replace('http://info.kingcounty.gov/', 'https://info.kingcounty.gov/')
+        if p.get('CurrentStatus') != 'Active' or not url.startswith('https://info.kingcounty.gov/'):
+            continue
+        lon, lat = f['geometry']['coordinates'][:2]
+        out.append(C('King County DOT', p['Location'], 'King County, WA', 'United States', lat, lon, url))
+    return sample(out, n)
+
+
+@source
+def drivebc(n):
+    d = get('https://www.drivebc.ca/api/webcams/').json()
+    out = []
+    for c in d:
+        if not c.get('is_on') or c.get('marked_stale') or not c.get('should_appear', True):
+            continue
+        lon, lat = c['location']['coordinates'][:2]
+        out.append(C('DriveBC', c['name'], c.get('region_name') or 'British Columbia', 'Canada', lat, lon, f"https://www.drivebc.ca/images/{c['id']}.jpg"))
+    return nearest(out, [(49.2827, -123.1207, 'Vancouver'), (48.4284, -123.3656, 'Victoria'), (50.1163, -122.9574, 'Whistler')], n)
+
+
+@source
+def calgary(n):
+    d = get('https://data.calgary.ca/resource/k7p9-kppz.json?$limit=500').json()
+    out = []
+    for c in d:
+        url = (c.get('camera_url') or {}).get('url', '').replace('http://', 'https://')
+        if not url.startswith('https://trafficcam.calgary.ca/'):
+            continue
+        lon, lat = c['point']['coordinates'][:2]
+        out.append(C('City of Calgary', c['camera_location'], 'Calgary', 'Canada', lat, lon, url))
+    return nearest(out, [(51.0461, -114.0626, 'Calgary')], n)
+
+
+@source
+def toronto(n):
+    t = get('https://opendata.toronto.ca/transportation/tmc/rescucameraimages/Data/tmcearthcameras.json').text
+    d = json.loads(t[t.index('(') + 1: t.rindex(')')])
+    out = [C('City of Toronto RESCU', c['Name'].title(), 'Toronto', 'Canada', c['Latitude'], c['Longitude'],
+             f"https://opendata.toronto.ca/transportation/tmc/rescucameraimages/CameraImages/loc{c['Number']}.jpg")
+           for c in d['Data'] if re.fullmatch(r'\d+', str(c['Number']))]
+    return nearest(out, [(43.6532, -79.3832, 'Toronto')], n)
+
+
+@source
+def txdot(n):
+    out = []
+    for code, city in [('HOU', 'Houston'), ('DAL', 'Dallas'), ('AUS', 'Austin'), ('SAT', 'San Antonio'), ('ELP', 'El Paso')]:
+        try:
+            d = get(f'https://its.txdot.gov/its/DistrictIts/GetCctvStatusListByDistrict?districtCode={code}').json()
+        except Exception as e:
+            print('txdot', code, e); continue
+        seen = set()
+        for rows in d['roadwayCctvStatuses'].values():
+            for r in rows:
+                if r.get('statusDescription') != 'Device Online' or r.get('hasSnapshot') is False or r['icd_Id'] in seen:
+                    continue
+                if not isinstance(r.get('latitude'), (int, float)) or not r['latitude']:
+                    continue
+                seen.add(r['icd_Id'])
+                url = 'https://its.txdot.gov/its/DistrictIts/GetCctvSnapshotByIcdId?' + requests.compat.urlencode({'icdId': r['icd_Id'], 'districtCode': code})
+                out.append(C('TxDOT ITS', r['name'], city, 'United States', r['latitude'], r['longitude'], url, kind='txdot'))
+    return nearest(out, [(29.7604, -95.3698, 'Houston'), (32.7767, -96.797, 'Dallas'), (29.4241, -98.4936, 'San Antonio'), (31.7619, -106.485, 'El Paso')], n)
+
+
+@source
+def austin(n):
+    d = get('https://data.austintexas.gov/api/views/b4k4-adkb/rows.json?accessType=DOWNLOAD').json()
+    cols = [c['fieldName'] for c in d['meta']['view']['columns']]
+    out = []
+    for row in d['data']:
+        r = dict(zip(cols, row))
+        if (r.get('camera_status') or '').strip().upper() != 'TURNED_ON':
+            continue
+        m = re.match(r'POINT \(([-\d.]+) ([-\d.]+)\)', r.get('location') or '')
+        if not m or not r.get('camera_id'):
+            continue
+        out.append(C('City of Austin', (r.get('location_name') or '').strip(), 'Austin', 'United States', m.group(2), m.group(1),
+                     f"https://cctv.austinmobility.io/image/{r['camera_id']}.jpg"))
+    return nearest(out, [(30.2672, -97.7431, 'Austin')], n)
+
+
+@source
+def fintraffic(n):
+    d = get('https://tie.digitraffic.fi/api/weathercam/v1/stations').json()
+    out = []
+    for f in d['features']:
+        p = f['properties']
+        if p.get('collectionStatus') != 'GATHERING':
+            continue
+        lon, lat = f['geometry']['coordinates'][:2]
+        for pr in p.get('presets', []):
+            if pr.get('inCollection'):
+                out.append(C('Fintraffic Digitraffic', p['name'].replace('_', ' '), '', 'Finland', lat, lon, f"https://weathercam.digitraffic.fi/{pr['id']}.jpg"))
+                break
+    return nearest(out, [(60.1699, 24.9384, 'Helsinki'), (61.4978, 23.761, 'Tampere'), (65.0121, 25.4651, 'Oulu'), (66.5039, 25.7294, 'Rovaniemi'), (60.4518, 22.2666, 'Turku')], n)
+
+
+@source
+def vegvesen(n):
+    d = get('https://ogckart-sn1.atlas.vegvesen.no/ogc/features/v1/collections/datex_3_1:CctvSimple/items?f=application/geo%2Bjson&limit=5000').json()
+    out = []
+    for f in d['features']:
+        p = f['properties']
+        url = p.get('stillImageUrl') or ''
+        if not url.startswith('https://kamera.atlas.vegvesen.no/api/images/'):
+            continue
+        lon, lat = f['geometry']['coordinates'][:2]
+        name = ' - '.join(x for x in [p.get('description'), p.get('roadNumber')] if x)
+        out.append(C('Statens vegvesen', name, '', 'Norway', lat, lon, url))
+    return nearest(out, [(59.9139, 10.7522, 'Oslo'), (60.3913, 5.3221, 'Bergen'), (63.4305, 10.3951, 'Trondheim'), (69.6492, 18.9553, 'Tromsø'), (58.97, 5.7331, 'Stavanger')], n)
+
+
+@source
+def tallinn(n):
+    d = json.load(open('/home/user/gods-eye-view/config/cctv_sources.tallinn.json'))
+    out = [C('City of Tallinn', c['name'], 'Tallinn', 'Estonia', c['lat'], c['lon'], c['snapshotUrl']) for c in d if c.get('snapshotUrl', '').startswith('https://ristmikud.tallinn.ee/')]
+    return sample(out, n)
+
+
+@source
+def tarktee(n):
+    ns = {'d': 'http://datex2.eu/schema/2/2_0'}
+    loc = ET.fromstring(get('https://tarktee.transpordiamet.ee/api/v1/datex/roadCameraLocations').content)
+    locs = {}
+    for pl in loc.iter('{http://datex2.eu/schema/2/2_0}predefinedLocation'):
+        lat = pl.find('.//d:latitude', ns); lon = pl.find('.//d:longitude', ns); nm = pl.find('.//d:value', ns)
+        if lat is not None and lon is not None:
+            locs[pl.get('id')] = (float(lat.text), float(lon.text), nm.text if nm is not None else '')
+    img = ET.fromstring(get('https://tarktee.transpordiamet.ee/api/v1/datex/roadCameraImages').content)
+    out = []
+    for tv in img.iter('{http://datex2.eu/schema/2/2_0}linearTrafficView'):
+        ref = tv.find('d:linearPredefinedLocationReference', ns)
+        u = tv.find('.//d:urlLinkAddress', ns)
+        if ref is None or u is None or ref.get('id') not in locs:
+            continue
+        lat, lon, nm = locs[ref.get('id')]
+        out.append(C('Transpordiamet Tarktee', nm, '', 'Estonia', lat, lon, u.text))
+    return nearest(out, [(59.437, 24.753, 'Tallinn'), (58.378, 26.729, 'Tartu'), (58.3859, 24.4971, 'Pärnu')], n)
+
+
+@source
+def lithuania(n):
+    rows = get('https://eismoinfo.lt/eismoinfo-backend/camera-info-table').json()
+    layer = get('https://eismoinfo.lt/eismoinfo-backend/layer-static-features/VKR').json()
+    feats = {str(f.get('id')): f for L in layer for f in L.get('features', [])}
+    out = []
+    for r in rows:
+        f = feats.get(str(r.get('id')))
+        try:
+            lat, lon = f['points'][0]['point']
+        except Exception:
+            continue
+        out.append(C('Via Lietuva eismoinfo', r['name'], '', 'Lithuania', lat, lon, f"https://eismoinfo.lt/eismoinfo-backend/image-provider/camera/last?id={r['id']}"))
+    return nearest(out, [(54.6872, 25.2797, 'Vilnius'), (54.8985, 23.9036, 'Kaunas'), (55.7033, 21.1443, 'Klaipėda')], n)
+
+
+@source
+def catalonia(n):
+    x = get('https://www.gencat.cat/transit/opendata/cameres.xml').text
+    out = []
+    for m in re.finditer(r'<gml:coordinates[^>]*>([-\d.]+),([-\d.]+)</gml:coordinates>.*?<cite:carretera>(.*?)</cite:carretera>.*?<cite:municipi>(.*?)</cite:municipi>.*?<cite:link>(.*?)</cite:link>.*?<cite:font>(.*?)</cite:font>', x, re.S):
+        lon, lat, road, muni, link, font = m.groups()
+        link = link.replace('&amp;', '&').replace('http://', 'https://')
+        if font not in ('SCT', 'IMI', 'Terrassa'):
+            continue
+        city = 'Barcelona' if font == 'IMI' else ('Terrassa' if font == 'Terrassa' else muni)
+        out.append(C('Servei Català de Trànsit', f'{road} {muni}', city, 'Spain', lat, lon, link))
+    return nearest(out, [(41.3874, 2.1686, 'Barcelona'), (41.5636, 2.0111, 'Terrassa'), (41.45, 2.2, 'Barcelona area')], n)
+
+
+@source
+def nsw(n):
+    d = get('https://data.livetraffic.com/cameras/traffic-cam.json').json()
+    out = []
+    for f in d['features']:
+        p = f['properties']
+        href = (p.get('href') or '').replace('http://', 'https://')
+        if not href.startswith('https://webcams.transport.nsw.gov.au/'):
+            continue
+        lon, lat = f['geometry']['coordinates'][:2]
+        out.append(C('Live Traffic NSW', p['title'], '', 'Australia', lat, lon, href))
+    return nearest(out, [(-33.8688, 151.2093, 'Sydney'), (-32.9283, 151.7817, 'Newcastle'), (-34.4278, 150.8931, 'Wollongong'), (-33.8, 151.0, 'Western Sydney')], n)
+
+
+@source
+def singapore(n):
+    d = get('https://api.data.gov.sg/v1/transport/traffic-images').json()
+    out = [C('LTA Singapore (data.gov.sg)', f"Camera {c['camera_id']}", 'Singapore', 'Singapore', c['location']['latitude'], c['location']['longitude'], c['image'])
+           for c in d['items'][0]['cameras']]
+    return sample(out, n)
+
+
+@source
+def hongkong(n):
+    x = ET.fromstring(get('https://static.data.gov.hk/td/traffic-snapshot-images/code/Traffic_Camera_Locations_En.xml').content)
+    out = []
+    for im in x.iter('image'):
+        g = lambda k: (im.findtext(k) or '').strip()
+        if not g('url').startswith('https://tdcctv.data.one.gov.hk/'):
+            continue
+        out.append(C('HK Transport Department', re.sub(r'\s*\[.*?\]$', '', g('description')), f"Hong Kong ({g('district')})", 'Hong Kong', g('latitude'), g('longitude'), g('url')))
+    return sample(out, n)
+
+
+@source
+def nz(n):
+    d = get('https://trafficnz.info/service/traffic/rest/4/cameras/all', headers={'Accept': 'application/json'}).json()
+    out = []
+    for c in d['response']['camera']:
+        if c.get('offline') or c.get('underMaintenance'):
+            continue
+        out.append(C('NZTA Waka Kotahi', (c.get('name') or '').strip() + (' - ' + c['description'] if c.get('description') else ''),
+                     (c.get('region') or {}).get('name', ''), 'New Zealand', c['latitude'], c['longitude'], 'https://trafficnz.info' + c['imageUrl']))
+    return nearest(out, [(-36.8485, 174.7633, 'Auckland'), (-41.2865, 174.7762, 'Wellington'), (-43.5321, 172.6362, 'Christchurch'), (-37.787, 175.279, 'Hamilton'), (-45.0312, 168.6626, 'Queenstown')], n)
+
+
+TARGETS = dict(nsw=26, hongkong=24, singapore=18, nz=20, nyc=20, caltrans=18, wsdot=12, kingco=6, drivebc=14, calgary=8,
+               toronto=10, txdot=10, austin=8, tfl=14, fintraffic=10, vegvesen=10, tallinn=6, tarktee=6, lithuania=8, catalonia=10)
+
+
+def fetch_frame(c):
+    try:
+        hdr = {}
+        if c['kind'] == 'txdot':
+            r = S.get(c['url'], timeout=30, headers={'Accept': 'application/json'})
+            r.raise_for_status()
+            js = r.json()
+            b64 = js.get('snippet') or js.get('Snippet') or ''
+            data = base64.b64decode(b64.split(',')[-1])
+        else:
+            r = S.get(c['url'], timeout=30)
+            r.raise_for_status()
+            data = r.content
+        im = Image.open(io.BytesIO(data))
+        im.load()
+        im = im.convert('RGB')
+        g = im.convert('L')
+        st = ImageStat.Stat(g)
+        edges = ImageStat.Stat(g.resize((320, 180)).filter(ImageFilter.FIND_EDGES)).mean[0]
+        sat = ImageStat.Stat(im.convert('HSV').split()[1]).mean[0]
+        small = g.resize((16, 9))
+        px = list(small.tobytes())
+        ahash = ''.join('1' if p > sum(px) / len(px) else '0' for p in px)
+        h = hashlib.md5(c['url'].encode()).hexdigest()[:12]
+        path = f'{WORK}/frames/{h}.jpg'
+        im.save(path, quality=95)
+        c.update(ok=True, file=path, w=im.width, h=im.height, mean=round(st.mean[0], 1), std=round(st.stddev[0], 1),
+                 edges=round(edges, 2), sat=round(sat, 1), ahash=ahash, bytes=len(data), fetched=time.strftime('%Y-%m-%dT%H:%M:%SZ', time.gmtime()))
+    except Exception as e:
+        c.update(ok=False, err=str(e)[:160])
+    return c
+
+
+if __name__ == '__main__':
+    only = sys.argv[2].split(',') if len(sys.argv) > 2 else list(SOURCES)
+    cands = []
+    for name in only:
+        try:
+            got = SOURCES[name](TARGETS.get(name, 8))
+            print(f'{name}: {len(got)} candidates')
+            for g in got:
+                g['src_key'] = name
+            cands += got
+        except Exception as e:
+            print(f'{name}: CATALOG FAILED {e}')
+    with ThreadPoolExecutor(24) as ex:
+        res = list(ex.map(fetch_frame, cands))
+    prev = []
+    pth = f'{WORK}/candidates.json'
+    if os.path.exists(pth):
+        prev = [p for p in json.load(open(pth)) if p['src_key'] not in only]
+    json.dump(prev + res, open(pth, 'w'), ensure_ascii=False, indent=0)
+    from collections import Counter
+    print('ok per source', Counter(c['src_key'] for c in res if c['ok']))
+    print('fail per source', Counter(c['src_key'] for c in res if not c['ok']))
+    for c in res:
+        if not c['ok']:
+            print('  FAIL', c['src_key'], c['url'][:90], c['err'][:100])

intro-sequence/tools/fetch/cctv_select.py

@@ -0,0 +1,42 @@
+#!/usr/bin/env python3
+"""Stage 2: pick a spread of good frames from cctv_fetch.py output, cover-crop to 640x360, write cctv/index.json.
+Usage: python3 -I cctv_select.py <work_dir> <out_cctv_dir>
+EXCLUDE lists frames rejected on visual review of the contact sheets (placeholders such as
+'Temporarily Unavailable', 'Kamera er midlertidig ute av drift', 'NB! ÜHENDUS KAAMERAGA PUUDUB',
+'Interrupció temporal de la imatge', and an all-black King County frame)."""
+import json, os, sys
+from collections import Counter
+from PIL import Image
+W, OUT = sys.argv[1], sys.argv[2]
+ok = json.load(open(f'{W}/ok.json'))
+EXCLUDE = {40, 43, 45, 46, 49, 66, 126, 139, 148, 150}
+PREFER = {'hongkong': [187, 195, 197, 198, 201, 205, 206, 196, 200, 202]}  # fewest privacy-mask polygons
+QUOTA = dict(nsw=12, hongkong=10, singapore=6, nz=12, nyc=9, caltrans=6, wsdot=6, kingco=3, drivebc=6, calgary=4, toronto=6,
+             txdot=4, austin=4, tfl=8, fintraffic=4, vegvesen=4, tallinn=3, tarktee=3, lithuania=4, catalonia=3)
+hash_count = Counter(x['ahash'] for x in ok)
+good = [x for x in ok if x['i'] not in EXCLUDE and hash_count[x['ahash']] == 1 and x['w'] >= 320 and x['mean'] > 25 and x['std'] > 15]
+pick = []
+for src, q in QUOTA.items():
+    pool = [x for x in good if x['src_key'] == src]
+    pref = [x for i in PREFER.get(src, []) for x in pool if x['i'] == i]
+    rest = sorted([x for x in pool if x not in pref], key=lambda x: -(x['std'] * x['edges']))
+    pick += (pref + rest)[:q]
+os.makedirs(OUT, exist_ok=True)
+for f in os.listdir(OUT):
+    if f.startswith('cam_') and f.endswith('.jpg'):
+        os.remove(os.path.join(OUT, f))
+index = []
+for n, x in enumerate(pick, 1):
+    im = Image.open(x['file']).convert('RGB')
+    w, h = im.size
+    s = max(640 / w, 360 / h)
+    im = im.resize((max(640, round(w * s)), max(360, round(h * s))), Image.LANCZOS)
+    w, h = im.size
+    l, t = (w - 640) // 2, (h - 360) // 2
+    im = im.crop((l, t, l + 640, t + 360))
+    fn = f'cam_{n:03d}.jpg'
+    im.save(os.path.join(OUT, fn), quality=88)
+    index.append(dict(file=fn, name=x['name'], city=x['city'], country=x['country'], lat=x['lat'], lon=x['lon'], source=x['source'],
+                      fetched_utc=x['fetched'], orig_size=[x['w'], x['h']], url=x['url']))
+json.dump(index, open(os.path.join(OUT, 'index.json'), 'w'), ensure_ascii=False, indent=1)
+print(len(index), Counter(i['country'] for i in index))

intro-sequence/tools/fetch/fetch_basic.sh

@@ -0,0 +1,33 @@
+#!/usr/bin/env bash
+# Re-fetch the raw keyless feeds used by process_basic.py / process_tle.py / process_vessels.py.
+# Usage: fetch_basic.sh <raw_dir>   then:
+#   python3 -I process_basic.py <raw_dir> ../../data
+#   python3 -I process_tle.py <raw_dir> ../../data
+#   python3 -I process_vessels.py <raw_dir> ../../data
+#   <venv with eccodes,numpy,requests>/python -I fetch_wind.py https://noaa-gfs-bdp-pds.s3.amazonaws.com/gfs.YYYYMMDD/HH/atmos/gfs.tHHz.pgrb2.1p00.f006 ../../data/wind.json
+#   python -I fetch_bonus.py ../../data <raw_dir>
+#   python -I cctv_fetch.py <work_dir> && python -I cctv_select.py <work_dir> ../../cctv   (after rebuilding ok.json/contact sheets and re-reviewing EXCLUDE)
+set -u
+R="$1"; mkdir -p "$R"; cd "$R"
+date -u +%Y-%m-%dT%H:%M:%SZ > fetch_start.txt
+CT='gods-eye-view-celestrak-proxy/1.0 (+https://github.com/bilawalsidhu/gods-eye-view)'  # CelesTrak 403s bulk groups without a descriptive UA
+f() { curl -sS -m 300 --compressed "${@:3}" -o "$1" -w "$1 %{http_code} %{size_download}\n" "$2"; }
+f opensky.json https://opensky-network.org/api/states/all &
+f mil.json https://api.adsb.lol/v2/mil &
+f mil_adsbfi.json https://opendata.adsb.fi/api/v2/mil &
+f quakes.geojson https://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/all_month.geojson &
+f viirs_snpp.csv https://firms.modaps.eosdis.nasa.gov/data/active_fire/suomi-npp-viirs-c2/csv/SUOMI_VIIRS_C2_Global_24h.csv &
+f viirs_n20.csv https://firms.modaps.eosdis.nasa.gov/data/active_fire/noaa-20-viirs-c2/csv/J1_VIIRS_C2_Global_24h.csv &
+f modis.csv https://firms.modaps.eosdis.nasa.gov/data/active_fire/modis-c6.1/csv/MODIS_C6_1_Global_24h.csv &
+f cables.json https://www.submarinecablemap.com/api/v3/cable/cable-geo.json &
+f coast50.geojson https://raw.githubusercontent.com/nvkelso/natural-earth-vector/master/geojson/ne_50m_coastline.geojson &
+f countries110.geojson https://raw.githubusercontent.com/nvkelso/natural-earth-vector/master/geojson/ne_110m_admin_0_countries.geojson &
+f places.geojson https://raw.githubusercontent.com/nvkelso/natural-earth-vector/master/geojson/ne_10m_populated_places_simple.geojson &
+f airports.csv https://davidmegginson.github.io/ourairports-data/airports.csv &
+f kystverket_ais.json https://kystdatahuset.kystverket.no/ws/api/ais/realtime/geojson &
+f dt_ais_from.json "https://meri.digitraffic.fi/api/ais/v1/locations?from=$(( ($(date +%s)-172800)*1000 ))" -H "Digitraffic-User: gods-eye-intro" &
+f digitraffic_vessels.json https://meri.digitraffic.fi/api/ais/v1/vessels -H "Digitraffic-User: gods-eye-intro" &
+wait
+# CelesTrak: sequential (parallel requests get connection resets); FORMAT=3le endpoint answered when FORMAT=tle timed out
+f tle_active3.txt "https://celestrak.org/NORAD/elements/gp.php?GROUP=active&FORMAT=3le" -A "$CT"
+for g in stations starlink gps-ops geo weather; do sleep 3; f tle_$g.txt "https://celestrak.org/NORAD/elements/gp.php?GROUP=$g&FORMAT=tle" -A "$CT"; done

intro-sequence/tools/fetch/fetch_bonus.py

@@ -0,0 +1,133 @@
+#!/usr/bin/env python3
+"""Bonus layers: radio stations (Radio Browser), GBFS bike stations, launch pads (Launch Library 2),
+power plants (WRI Global Power Plant Database).  Usage: python3 -I fetch_bonus.py <out_data_dir> <raw_dir>"""
+import csv, io, json, os, sys, time, zipfile
+import requests
+
+OUT, RAW = sys.argv[1], sys.argv[2]
+only = sys.argv[3].split(',') if len(sys.argv) > 3 else ['radio', 'gbfs', 'pads', 'power']
+S = requests.Session()
+S.headers['User-Agent'] = 'GodsEyeView/1.0 intro-sequence data snapshot'
+log = {}
+
+
+def dump(name, obj):
+    with open(os.path.join(OUT, name), 'w') as f:
+        json.dump(obj, f, separators=(',', ':'), ensure_ascii=False)
+
+
+if 'radio' in only:
+    rows, used = [], None
+    for host in ['https://de1.api.radio-browser.info', 'https://de2.api.radio-browser.info', 'https://nl1.api.radio-browser.info']:
+        try:
+            r = S.get(f'{host}/json/stations/search', params={'has_geo_info': 'true', 'hidebroken': 'true', 'limit': 100000}, timeout=180,
+                      headers={'User-Agent': 'GodsEyeView/1.0 (Radio Browser directory client)'})
+            r.raise_for_status()
+            data = r.json(); used = host
+            break
+        except Exception as e:
+            print('radio', host, e)
+    seen = set()
+    for s in data:
+        lat, lon = s.get('geo_lat'), s.get('geo_long')
+        if lat is None or lon is None or (abs(lat) < 0.01 and abs(lon) < 0.01):
+            continue
+        key = (round(lon, 3), round(lat, 3), s['name'].strip())
+        if key in seen:
+            continue
+        seen.add(key)
+        rows.append([round(lon, 4), round(lat, 4), s['name'].strip(), s.get('countrycode') or ''])
+    dump('radio.json', {'cols': ['lon', 'lat', 'name', 'cc'], 'rows': rows})
+    log['radio'] = dict(url=f'{used}/json/stations/search?has_geo_info=true&hidebroken=true&limit=100000', rows=len(rows))
+    print('radio', len(rows))
+
+if 'gbfs' in only:
+    SYSTEMS = {
+        'Citi Bike (New York)': 'https://gbfs.lyft.com/gbfs/2.3/bkn/en/station_information.json',
+        'Divvy (Chicago)': 'https://gbfs.lyft.com/gbfs/2.3/chi/en/station_information.json',
+        'Bay Wheels (SF Bay)': 'https://gbfs.lyft.com/gbfs/2.3/bay/en/station_information.json',
+        'Capital Bikeshare (DC)': 'https://gbfs.lyft.com/gbfs/2.3/dca-cabi/en/station_information.json',
+        'Bluebikes (Boston)': 'https://gbfs.bluebikes.com/gbfs/en/station_information.json',
+        'Bike Share Toronto': 'https://toronto.publicbikesystem.net/customer/gbfs/v2/en/station_information.json',
+        'BIXI (Montreal)': 'https://gbfs.velobixi.com/gbfs/en/station_information.json',
+        'Ecobici (Mexico City)': 'https://gbfs.mex.lyftbikes.com/gbfs/en/station_information.json',
+        'Velib Metropole (Paris)': 'https://velib-metropole-opendata.smovengo.cloud/opendata/Velib_Metropole/station_information.json',
+        'Bicing (Barcelona)': 'https://barcelona.publicbikesystem.net/customer/gbfs/v2/en/station_information.json',
+        'BiciMAD (Madrid)': 'https://madrid.publicbikesystem.net/customer/gbfs/v2/en/station_information.json',
+        'Bike Sampa (Sao Paulo)': 'https://saopaulo.publicbikesystem.net/customer/gbfs/v2/en/station_information.json',
+        'Bike Rio (Rio de Janeiro)': 'https://riodejaneiro.publicbikesystem.net/customer/gbfs/v2/en/station_information.json',
+        'Bike Santiago': 'https://santiago.publicbikesystem.net/customer/gbfs/v2/en/station_information.json',
+        'Tembici Bogota': 'https://bogota.publicbikesystem.net/customer/gbfs/v2/en/station_information.json',
+        'Indego (Philadelphia)': 'https://gbfs.bcycle.com/bcycle_indego/station_information.json',
+        'Metro Bike Share (LA)': 'https://gbfs.bcycle.com/bcycle_lametro/station_information.json',
+        'Oslo Bysykkel': 'https://gbfs.urbansharing.com/oslobysykkel.no/station_information.json',
+    }
+    rows, per = [], {}
+    for name, url in SYSTEMS.items():
+        try:
+            d = S.get(url, timeout=60, headers={'Client-Identifier': 'gods-eye-view'}).json()
+            st = d['data']['stations']
+            for s in st:
+                rows.append([round(float(s['lon']), 5), round(float(s['lat']), 5)])
+            per[name] = len(st)
+        except Exception as e:
+            per[name] = f'FAILED {str(e)[:80]}'
+    # nextbike: one keyless global live feed covering every nextbike city
+    try:
+        d = S.get('https://api.nextbike.net/maps/nextbike-live.json', timeout=120).json()
+        n = 0
+        for c in d['countries']:
+            for city in c.get('cities', []):
+                for p in city.get('places', []):
+                    if p.get('spot'):  # stations only, not free-floating bikes
+                        rows.append([round(p['lng'], 5), round(p['lat'], 5)]); n += 1
+        per['nextbike (all cities, global)'] = n
+    except Exception as e:
+        per['nextbike'] = f'FAILED {e}'
+    dump('bikes.json', {'cols': ['lon', 'lat'], 'systems': per, 'rows': rows})
+    log['gbfs'] = dict(systems=per, urls=list(SYSTEMS.values()) + ['https://api.nextbike.net/maps/nextbike-live.json'], rows=len(rows))
+    print('bikes', len(rows), per)
+
+if 'pads' in only:
+    url = 'https://ll.thespacedevs.com/2.3.0/pads/?limit=100&mode=list'
+    rows = []
+    while url:
+        r = S.get(url, timeout=60)
+        r.raise_for_status()
+        d = r.json()
+        for p in d['results']:
+            try:
+                lat, lon = float(p['latitude']), float(p['longitude'])
+            except (TypeError, ValueError, KeyError):
+                continue
+            loc = p.get('location') or {}
+            rows.append([round(lon, 4), round(lat, 4), p['name'], loc.get('name') if isinstance(loc, dict) else None,
+                         p.get('total_launch_count') or 0, bool(p.get('active'))])
+        url = d.get('next')
+        time.sleep(1)
+    rows.sort(key=lambda x: -x[4])
+    dump('launch_sites.json', {'cols': ['lon', 'lat', 'pad', 'location', 'total_launches', 'active'], 'rows': rows})
+    log['pads'] = dict(url='https://ll.thespacedevs.com/2.3.0/pads/?limit=100&mode=list (paged)', rows=len(rows))
+    print('pads', len(rows))
+
+if 'power' in only:
+    url = 'https://raw.githubusercontent.com/wri/global-power-plant-database/master/output_database/global_power_plant_database.csv'
+    r = S.get(url, timeout=180)
+    r.raise_for_status()
+    rows = []
+    for row in csv.DictReader(io.StringIO(r.content.decode('utf-8'))):
+        try:
+            rows.append([round(float(row['longitude']), 4), round(float(row['latitude']), 4), round(float(row['capacity_mw']), 1), row['primary_fuel'], row['name'], row['country']])
+        except ValueError:
+            pass
+    rows.sort(key=lambda x: -x[2])
+    dump('power_plants.json', {'cols': ['lon', 'lat', 'capacity_mw', 'fuel', 'name', 'iso3'], 'rows': rows})
+    log['power'] = dict(url=url, rows=len(rows))
+    print('power', len(rows))
+
+prev = {}
+p = os.path.join(RAW, 'bonus_log.json')
+if os.path.exists(p):
+    prev = json.load(open(p))
+prev.update(log)
+json.dump(prev, open(p, 'w'), indent=1)

intro-sequence/tools/fetch/fetch_wind.py

@@ -0,0 +1,28 @@
+#!/usr/bin/env python3
+"""GFS 1.0 deg 10 m wind U/V from NOAA's AWS Open Data bucket (noaa-gfs-bdp-pds) via .idx byte
+ranges, same approach as server/providers/wind/gfs.js; decoded with python `eccodes` (pip).
+Usage: python fetch_wind.py <gfs file base url (no .idx)> <out wind.json>"""
+import json, sys, requests, numpy as np, eccodes
+base, out = sys.argv[1], sys.argv[2]
+lines = [l.split(':') for l in requests.get(base + '.idx', timeout=60).text.strip().split('\n')]
+def field(var):
+    i = next(k for k, p in enumerate(lines) if p[3] == var and p[4] == '10 m above ground')
+    s, e = int(lines[i][1]), int(lines[i + 1][1]) - 1
+    b = requests.get(base, headers={'Range': f'bytes={s}-{e}'}, timeout=120).content
+    h = eccodes.codes_new_from_message(b)
+    g = {k: eccodes.codes_get(h, k) for k in ['Ni', 'Nj', 'dataDate', 'dataTime', 'step']}
+    g.update({k: eccodes.codes_get_double(h, k) for k in ['longitudeOfFirstGridPointInDegrees', 'latitudeOfFirstGridPointInDegrees', 'iDirectionIncrementInDegrees', 'jDirectionIncrementInDegrees']})
+    g['values'] = eccodes.codes_get_values(h).reshape(g['Nj'], g['Ni'])
+    eccodes.codes_release(h)
+    return g
+U, V = field('UGRD'), field('VGRD')
+assert U['longitudeOfFirstGridPointInDegrees'] == 0 and U['latitudeOfFirstGridPointInDegrees'] == 90
+dx = U['iDirectionIncrementInDegrees']; shift = int(round(180 / dx))
+u = np.roll(U['values'], -shift, axis=1); v = np.roll(V['values'], -shift, axis=1)  # lon 0..359 -> -180..179
+ny, nx = u.shape
+json.dump({'source': 'NOAA GFS 1.0deg ' + base.split('/')[-1], 'refTime': f"{U['dataDate']} {U['dataTime']:04d}Z", 'forecastHour': U['step'],
+           'level': '10 m above ground', 'units': 'm/s', 'nx': nx, 'ny': ny, 'lo1': -180, 'la1': 90, 'dx': dx, 'dy': U['jDirectionIncrementInDegrees'],
+           'u': [round(float(x), 2) for x in u.ravel()], 'v': [round(float(x), 2) for x in v.ravel()]},
+          open(out, 'w'), separators=(',', ':'))
+sp = np.hypot(u, v)
+print(nx, ny, 'max', sp.max().round(1), 'mean', sp.mean().round(2), U['dataDate'], U['dataTime'], 'f', U['step'])

intro-sequence/tools/fetch/process_basic.py

@@ -0,0 +1,172 @@
+#!/usr/bin/env python3
+"""Convert raw fetched feeds (see fetch_basic.sh) into compact intro-sequence JSON.
+
+Usage: python3 -I process_basic.py <raw_dir> <out_data_dir>
+All inputs are real downloads; this only filters, reprojects units and rounds.
+"""
+import csv, json, os, sys, time
+
+RAW, OUT = sys.argv[1], sys.argv[2]
+meta = {}
+
+
+def r(x, n):
+    return None if x is None else round(float(x), n)
+
+
+def dump(name, obj):
+    p = os.path.join(OUT, name)
+    with open(p, 'w') as f:
+        json.dump(obj, f, separators=(',', ':'), ensure_ascii=False)
+    print(f'{name}: {os.path.getsize(p)/1e6:.2f} MB')
+
+
+def raw(name):
+    return os.path.join(RAW, name)
+
+
+# 1. flights (OpenSky)
+o = json.load(open(raw('opensky.json')))
+rows = []
+for s in o['states']:
+    lon, lat, on_ground = s[5], s[6], s[8]
+    if lon is None or lat is None or on_ground:
+        continue
+    alt = s[13] if s[13] is not None else s[7]
+    rows.append([r(lon, 4), r(lat, 4), r(alt, 0), r(s[10], 1), r(s[9], 1),
+                 (s[1] or '').strip(), s[2]])
+dump('flights.json', {'t': o['time'], 'cols': ['lon', 'lat', 'alt_m', 'track_deg', 'vel_ms', 'callsign', 'country'], 'rows': rows})
+meta['flights'] = len(rows)
+
+# 2. military (adsb.lol /v2/mil, unioned with adsb.fi /v2/mil, dedup by hex; adsb.lol wins)
+FT, KT = 0.3048, 0.514444
+seen, rows, tmax = set(), [], 0
+for fname in ['mil.json', 'mil_adsbfi.json']:
+    if not os.path.exists(raw(fname)):
+        continue
+    d = json.load(open(raw(fname)))
+    tmax = max(tmax, int((d.get('now') or 0) / (1000 if (d.get('now') or 0) > 1e11 else 1)))
+    for a in d.get('ac') or d.get('aircraft') or []:
+        lat, lon = a.get('lat'), a.get('lon')
+        if lat is None or lon is None or a['hex'] in seen:
+            continue
+        alt = a.get('alt_geom', a.get('alt_baro'))
+        if a.get('alt_baro') == 'ground' or alt == 'ground':
+            continue  # airborne only
+        seen.add(a['hex'])
+        track = a.get('track', a.get('true_heading'))
+        gs = a.get('gs')
+        rows.append([r(lon, 4), r(lat, 4), r(alt * FT, 0) if isinstance(alt, (int, float)) else None,
+                     r(track, 1), r(gs * KT, 1) if gs is not None else None,
+                     (a.get('flight') or '').strip(), None, a.get('t')])
+dump('military.json', {'t': tmax, 'cols': ['lon', 'lat', 'alt_m', 'track_deg', 'vel_ms', 'callsign', 'country', 'type'], 'rows': rows,
+                       'note': 'country not provided by adsb.lol/adsb.fi feeds (null)'})
+meta['military'] = len(rows)
+
+# 4. quakes
+q = json.load(open(raw('quakes.geojson')))
+rows = []
+for f in q['features']:
+    c, p = f['geometry']['coordinates'], f['properties']
+    if p.get('mag') is None:
+        continue
+    rows.append([r(c[0], 3), r(c[1], 3), r(c[2], 1), r(p['mag'], 2), p['time'], p.get('place') or ''])
+rows.sort(key=lambda x: x[4])
+dump('quakes.json', {'t': q['metadata']['generated'], 'cols': ['lon', 'lat', 'depth_km', 'mag', 'time_ms', 'place'], 'rows': rows})
+meta['quakes'] = len(rows)
+
+# 5. fires (FIRMS 24h global: SNPP VIIRS, NOAA-20 VIIRS, MODIS)
+rows, per = [], {}
+for fname, bcol, tag in [('viirs_snpp.csv', 'bright_ti4', 'VIIRS_SNPP'), ('viirs_n20.csv', 'bright_ti4', 'VIIRS_NOAA20'), ('modis.csv', 'brightness', 'MODIS')]:
+    if not os.path.exists(raw(fname)):
+        continue
+    n = 0
+    with open(raw(fname), newline='') as fh:
+        for row in csv.DictReader(fh):
+            try:
+                rows.append([r(row['longitude'], 3), r(row['latitude'], 3), r(row['frp'], 1), r(row[bcol], 1)])
+                n += 1
+            except (KeyError, ValueError):
+                pass
+    per[tag] = n
+dump('fires.json', {'cols': ['lon', 'lat', 'frp', 'brightness'], 'sources': per, 'rows': rows})
+meta['fires'] = len(rows)
+meta['fires_per'] = per
+
+# 8. cables
+c = json.load(open(raw('cables.json')))
+lines = []
+for f in c['features']:
+    g = f['geometry']
+    parts = g['coordinates'] if g['type'] == 'MultiLineString' else [g['coordinates']]
+    for part in parts:
+        pl = [[r(x, 2), r(y, 2)] for x, y in (pt[:2] for pt in part)]
+        if len(pl) >= 2:
+            lines.append(pl)
+dump('cables.json', {'cables': lines})
+meta['cables'] = (len(c['features']), len(lines))
+
+
+# 9. coastline + borders
+def lines_of(geo):
+    out = []
+    for f in geo['features']:
+        g = f['geometry']
+        if g is None:
+            continue
+        t, co = g['type'], g['coordinates']
+        if t == 'LineString':
+            parts = [co]
+        elif t == 'MultiLineString':
+            parts = co
+        elif t == 'Polygon':
+            parts = co
+        elif t == 'MultiPolygon':
+            parts = [ring for poly in co for ring in poly]
+        else:
+            parts = []
+        for part in parts:
+            pl, last = [], None
+            for x, y in (pt[:2] for pt in part):
+                pt = [r(x, 2), r(y, 2)]
+                if pt != last:
+                    pl.append(pt)
+                last = pt
+            if len(pl) >= 2:
+                out.append(pl)
+    return out
+
+
+coast = lines_of(json.load(open(raw('coast50.geojson'))))
+dump('coastline.json', {'lines': coast})
+borders = lines_of(json.load(open(raw('countries110.geojson'))))
+dump('borders.json', {'lines': borders})
+meta['coast'] = len(coast)
+meta['borders'] = len(borders)
+
+# 10. cities
+pp = json.load(open(raw('places.geojson')))
+rows = []
+for f in pp['features']:
+    p = f['properties']
+    lon, lat = f['geometry']['coordinates'][:2]
+    rows.append([r(lon, 3), r(lat, 3), int(p.get('pop_max') or 0), p.get('name') or p.get('nameascii'), p.get('adm0name') or p.get('sov0name')])
+rows.sort(key=lambda x: -x[2])
+rows = rows[:3000]
+dump('cities.json', {'cols': ['lon', 'lat', 'pop_max', 'name', 'country'], 'rows': rows})
+meta['cities'] = len(rows)
+
+# 11. airports (OurAirports large + medium)
+rows = []
+with open(raw('airports.csv'), newline='', encoding='utf-8') as fh:
+    for row in csv.DictReader(fh):
+        if row['type'] not in ('large_airport', 'medium_airport'):
+            continue
+        rows.append([r(row['longitude_deg'], 4), r(row['latitude_deg'], 4), row['iata_code'] or row['ident'], row['name'],
+                     'L' if row['type'] == 'large_airport' else 'M'])
+rows.sort(key=lambda x: x[4])
+dump('airports.json', {'cols': ['lon', 'lat', 'iata', 'name', 'size'], 'rows': rows})
+meta['airports'] = (len(rows), sum(1 for x in rows if x[4] == 'L'))
+
+json.dump(meta, open(os.path.join(RAW, 'meta_basic.json'), 'w'))
+print(meta)

intro-sequence/tools/fetch/process_tle.py

@@ -0,0 +1,31 @@
+#!/usr/bin/env python3
+"""tle.txt (3-line TLEs, CelesTrak GROUP=active) + tle_groups.json (NORAD ids per group).
+Usage: python3 -I process_tle.py <raw_dir> <out_dir>"""
+import json, os, sys
+RAW, OUT = sys.argv[1], sys.argv[2]
+def parse(path):
+    L = [l.rstrip() for l in open(path) if l.strip()]
+    out = []
+    i = 0
+    while i + 2 < len(L) + 0 and i + 2 <= len(L) - 1:
+        if L[i+1].startswith('1 ') and L[i+2].startswith('2 '):
+            name = L[i][2:] if L[i].startswith('0 ') else L[i]
+            out.append((name.strip(), L[i+1], L[i+2])); i += 3
+        else:
+            i += 1
+    return out
+act = parse(os.path.join(RAW, 'tle_active3.txt'))
+with open(os.path.join(OUT, 'tle.txt'), 'w') as f:
+    for n, a, b in act:
+        f.write(f'{n}\n{a}\n{b}\n')
+groups, notable = {}, {}
+for g in ['stations', 'starlink', 'gps-ops', 'geo', 'weather']:
+    p = os.path.join(RAW, f'tle_{g}.txt')
+    if os.path.exists(p) and os.path.getsize(p) > 0:
+        sats = parse(p)
+        groups[g] = sorted(int(a[2:7]) for _, a, _ in sats)
+        for n, _, _ in sats[: (40 if g != 'starlink' else 3)]:
+            notable[n] = g
+epochs = sorted(a[18:32] for _, a, _ in act)
+json.dump({'groups_norad': groups, 'notable': notable}, open(os.path.join(OUT, 'tle_groups.json'), 'w'), separators=(',', ':'))
+print(len(act), {k: len(v) for k, v in groups.items()}, 'epoch range', epochs[0], epochs[-1])

intro-sequence/tools/fetch/process_vessels.py

@@ -0,0 +1,38 @@
+#!/usr/bin/env python3
+"""vessels.json from keyless AIS: Fintraffic Digitraffic (Finland/Baltic) + Kystverket Kystdatahuset realtime (Norway).
+Usage: python3 -I process_vessels.py <raw_dir> <out_dir>"""
+import json, os, sys, time
+RAW, OUT = sys.argv[1], sys.argv[2]
+rows, src = {}, {}
+# Norway (Kystverket) - LineString trails, last coordinate = latest position
+k = json.load(open(os.path.join(RAW, 'kystverket_ais.json')))
+for f in k['features']:
+    c, p = f['geometry']['coordinates'], f['properties']
+    if not c:
+        continue
+    lon, lat = c[-1]
+    cog = p.get('cog')
+    cog = None if cog is None or cog >= 360 else round(cog, 1)
+    sog = p.get('speed')
+    sog = None if sog is None or sog >= 102.3 else round(sog, 1)
+    rows[p['mmsi']] = [round(lon, 4), round(lat, 4), sog, cog, p['mmsi'], (p.get('ship_name') or '').strip() or None]
+    src[p['mmsi']] = 'NO'
+# Finland / Baltic (Digitraffic)
+names = {v['mmsi']: (v.get('name') or '').strip() or None for v in json.load(open(os.path.join(RAW, 'digitraffic_vessels.json')))}
+d = json.load(open(os.path.join(RAW, 'dt_ais_from.json')))
+for f in d['features']:
+    p = f['properties']
+    lon, lat = f['geometry']['coordinates'][:2]
+    if p['mmsi'] in rows:
+        continue
+    cog = p.get('cog'); cog = None if cog is None or cog >= 360 else round(cog, 1)
+    sog = p.get('sog'); sog = None if sog is None or sog >= 102.3 else round(sog, 1)
+    rows[p['mmsi']] = [round(lon, 4), round(lat, 4), sog, cog, p['mmsi'], names.get(p['mmsi'])]
+    src[p['mmsi']] = 'FI'
+out = list(rows.values())
+json.dump({'t': int(time.time()), 'cols': ['lon', 'lat', 'sog_kn', 'cog_deg', 'mmsi', 'name'],
+           'coverage': 'Norwegian coast/EEZ (Kystverket) + Finnish waters & Baltic Sea (Fintraffic Digitraffic); not global',
+           'counts': {'kystverket_norway': sum(1 for v in src.values() if v == 'NO'), 'digitraffic_finland_baltic': sum(1 for v in src.values() if v == 'FI')},
+           'rows': out}, open(os.path.join(OUT, 'vessels.json'), 'w'), separators=(',', ':'), ensure_ascii=False)
+lons = [r[0] for r in out]; lats = [r[1] for r in out]
+print(len(out), 'bbox', min(lons), max(lons), min(lats), max(lats))

intro-sequence/tools/finalize-v2.sh

@@ -0,0 +1,23 @@
+#!/usr/bin/env bash
+# v2: sound design only (made to sit under a music track). Normalise the SFX
+# mix to -16 LUFS, keep it as a stem, and mux share + master cuts.
+set -euo pipefail
+cd "$(dirname "$0")/.."
+node tools/export-cues.mjs
+python3 audio/sfx.py
+stats=$(ffmpeg -hide_banner -i audio/sfx.wav -af loudnorm=I=-16:TP=-1.5:LRA=14:print_format=json -f null - 2>&1 | sed -n '/^{/,/^}/p')
+g() { echo "$stats" | python3 -c "import json,sys;print(json.load(sys.stdin)['$1'])"; }
+ffmpeg -y -loglevel error -i audio/sfx.wav -af "loudnorm=I=-16:TP=-1.5:LRA=14:measured_I=$(g input_i):measured_TP=$(g input_tp):measured_LRA=$(g input_lra):measured_thresh=$(g input_thresh):linear=true,aresample=48000" -c:a pcm_s24le audio/sfx_norm.wav
+mkdir -p out/final_v2
+cp audio/sfx_norm.wav out/final_v2/GodsEyeView_FirstLight_v2_SFX_stem.wav
+for tag in 16x9 9x16; do
+  v=out/v2_video_$tag.mp4
+  [ -s "$v" ] || { echo "missing $v"; continue; }
+  ffmpeg -y -loglevel error -i $v -i audio/sfx_norm.wav -map 0:v -map 1:a -c:v copy -c:a aac -b:a 320k -shortest -movflags +faststart out/final_v2/GodsEyeView_FirstLight_v2_${tag}_master.mp4
+  ffmpeg -y -loglevel error -i $v -c:v libx264 -preset slow -b:v 16M -maxrate 24M -bufsize 32M -pass 1 -passlogfile out/final_v2/p_$tag -an -f null /dev/null
+  ffmpeg -y -loglevel error -i $v -i audio/sfx_norm.wav -map 0:v -map 1:a -c:v libx264 -preset slow -b:v 16M -maxrate 24M -bufsize 32M -pass 2 -passlogfile out/final_v2/p_$tag \
+    -pix_fmt yuv420p -colorspace bt709 -color_primaries bt709 -color_trc bt709 -c:a aac -b:a 256k -shortest -movflags +faststart out/final_v2/GodsEyeView_FirstLight_v2_${tag}.mp4
+  rm -f out/final_v2/p_$tag*
+  echo "finalized $tag"
+done
+ls -la out/final_v2

intro-sequence/tools/finalize.sh

@@ -0,0 +1,26 @@
+#!/usr/bin/env bash
+# Loudness-normalise the score (-14 LUFS, -1 dBTP) and mux it into both cuts.
+#   tools/finalize.sh            (after tools/render-all.sh has produced out/video_*.mp4)
+set -euo pipefail
+cd "$(dirname "$0")/.."
+python3 audio/score.py
+# two-pass loudnorm
+stats=$(ffmpeg -hide_banner -i audio/score.wav -af loudnorm=I=-14:TP=-1:LRA=11:print_format=json -f null - 2>&1 | sed -n '/^{/,/^}/p')
+mi=$(echo "$stats" | python3 -c "import json,sys;d=json.load(sys.stdin);print(d['input_i'])")
+mtp=$(echo "$stats" | python3 -c "import json,sys;d=json.load(sys.stdin);print(d['input_tp'])")
+mlra=$(echo "$stats" | python3 -c "import json,sys;d=json.load(sys.stdin);print(d['input_lra'])")
+mth=$(echo "$stats" | python3 -c "import json,sys;d=json.load(sys.stdin);print(d['input_thresh'])")
+ffmpeg -y -loglevel error -i audio/score.wav -af "loudnorm=I=-14:TP=-1:LRA=11:measured_I=$mi:measured_TP=$mtp:measured_LRA=$mlra:measured_thresh=$mth:linear=true,aresample=48000" -c:a pcm_s24le audio/score_norm.wav
+mkdir -p out/final
+for tag in 16x9 9x16; do
+  [ -s out/video_$tag.mp4 ] || { echo "missing out/video_$tag.mp4"; continue; }
+  # master: the CRF 14 picture untouched + 320k AAC
+  ffmpeg -y -loglevel error -i out/video_$tag.mp4 -i audio/score_norm.wav -map 0:v -map 1:a -c:v copy -c:a aac -b:a 320k -ar 48000 -shortest -movflags +faststart \
+    -metadata title="God's Eye View — First Light ($tag)" out/final/GodsEyeView_FirstLight_${tag}_master.mp4
+  # delivery: lighter encode for posting/sharing
+  ffmpeg -y -loglevel error -i out/video_$tag.mp4 -i audio/score_norm.wav -map 0:v -map 1:a -c:v libx264 -preset slow -crf 19 -tune grain -pix_fmt yuv420p \
+    -colorspace bt709 -color_primaries bt709 -color_trc bt709 -c:a aac -b:a 256k -ar 48000 -shortest -movflags +faststart \
+    -metadata title="God's Eye View — First Light ($tag)" out/final/GodsEyeView_FirstLight_${tag}.mp4
+  echo "finalized $tag"
+done
+ls -la out/final

intro-sequence/tools/flurry/build.py

@@ -0,0 +1,175 @@
+"""Build the flurry montage captures.
+
+  python3 select_cities.py   # -> city_candidates.json (primary + backup per region)
+  python3 build.py           # -> imagery/flurry/fx_###.jpg, index.json, tools/flurry/sheet.jpg
+
+Each capture: Esri World Imagery, 3x3 tiles around the point, centred 512x512
+crop, JPEG q86. Placeholder / low-variance captures are rejected automatically
+(tiles.quality_ok); captures that passed the metrics but looked wrong on the
+review sheets (forest, farmland, haze) are listed in VISUAL_REJECT. Rejected
+items are replaced by the next backup of the same region (cities) or by the
+next backup landmark.
+"""
+import glob
+import json
+import os
+import sys
+from concurrent.futures import ThreadPoolExecutor
+
+from PIL import Image
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from landmarks import LANDMARKS  # noqa: E402
+from tiles import HERE, MAX_WORKERS, OUT, capture, quality_ok  # noqa: E402
+
+N_CITIES = 170
+N_LANDMARKS = 90
+
+# Natural Earth points that landed on a park/water/cemetery: moved to the dense centre.
+CITY_OVERRIDES = {
+    "Lagos": (6.4541, 3.3947),          # Lagos Island (was open lagoon)
+    "Cairns": (-16.9230, 145.7740),     # CBD (was mangrove mudflat)
+    "Calgary": (51.0460, -114.0650),    # downtown (was cemetery)
+    "Dubai": (25.0805, 55.1403),        # Dubai Marina (was construction lot)
+    "Perth": (-31.9530, 115.8575),      # CBD (was Kings Park bush)
+    "Dhaka": (23.7330, 90.4172),        # Motijheel (was hazy open ground)
+    "Delhi": (28.6315, 77.2167),        # Connaught Place
+    "Montréal": (45.5017, -73.5673),    # downtown (was Mount Royal park)
+    "Busan": (35.1000, 129.0350),       # Nampo / harbour (was forested hill)
+    "Jeddah": (21.4858, 39.1925),       # Al-Balad old town (was empty lot)
+    "Tokyo": (35.6717, 139.7650),       # Ginza (was Imperial Palace woods)
+}
+VISUAL_REJECT = {
+    "Venice": "blurry low-res imagery",
+    "Conakry": "heavy haze",
+    "Maracaibo": "farmland / scrub",
+    "Barquisimeto": "dry riverbed, no city",
+    "Natal": "solid forest canopy",
+    "João Pessoa": "forest canopy",
+    "Mbuji-Mayi": "forest/scrub",
+    "Huambo": "scrub, sparse",
+    "Port Harcourt": "haze",
+    "Qaraghandy": "dark featureless rail yard",
+    "Herat": "low-res blur",
+    "Chengdu": "smog haze",
+    "Xian": "washed-out industrial lot",
+    "Kaohsiung": "forested hill",
+    "Sapporo": "university farm fields",
+    "Isfahan": "low contrast blur",
+    "Stuttgart": "hazy woodland",
+    "Townsville": "airport apron, not city",
+}
+LANDMARK_BACKUPS = [
+    "Glen Canyon Dam", "Grand Coulee Dam", "Mount St. Helens", "Groom Lake", "Diavik Diamond Mine",
+    "Syncrude Mildred Lake oil sands", "Centre-pivot fields, Kansas", "Indianapolis Motor Speedway",
+    "Brooklyn Bridge", "Panama Canal, Miraflores Locks", "Escondida Mine", "ALMA Observatory",
+    "Meeting of the Waters, Manaus", "Brasilia, National Congress", "PS10 / PS20 Solar Towers", "Tower Bridge",
+    "Port of Tema", "Akosombo Dam", "Okavango Delta", "FNB Stadium, Soweto", "East Oweinat pivots",
+    "Kilimanjaro, Kibo crater", "Ras Laffan Industrial City", "Dubai International Airport", "Bagan temples",
+    "Jiuquan Launch Centre", "Mount Bromo", "Vostochny Cosmodrome", "Pine Gap", "Tanegashima Space Center",
+    "Teide", "Faa'a International Airport", "Hartsfield-Jackson Atlanta Airport", "Niagara Horseshoe Falls",
+    "Iguazu Falls, Devil's Throat", "Vandenberg SLC-4E", "Paranal Observatory", "Cerro Dominador Solar",
+    "Gibraltar Airport runway", "Erg Chebbi dunes", "Millau Viaduct", "Garzweiler Lignite Mine", "Inga Dams",
+    "Grand Ethiopian Renaissance Dam", "Ras Tanura refinery", "Udachnaya Pipe", "Busan New Port",
+    "Mount Taranaki", "Beijing National Stadium", "Port of Hamburg, Burchardkai", "Port of Santos",
+    "Jebel Ali Port", "Mont-Saint-Michel", "Angkor Wat", "Mount Vesuvius", "Horseshoe Bend",
+    "Benban Solar Park", "Borobudur", "Bhadla Solar Park", "Kariba Dam", "Wake Island Airfield",
+    "Diamond Head", "Port Hedland salt ponds",
+]
+
+
+def evaluate(cands):
+    def job(c):
+        try:
+            img, info = capture(c["lat"], c["lon"], c["zoom"])
+            ok, why = quality_ok(info)
+        except Exception as e:  # network failure counts as a reject
+            img, info, ok, why = None, {}, False, f"fetch error: {e}"
+        if ok and c["name"] in VISUAL_REJECT and c.get("kind") == "city":
+            ok, why = False, "visual: " + VISUAL_REJECT[c["name"]]
+        return img, ok, why
+
+    with ThreadPoolExecutor(MAX_WORKERS) as ex:
+        return list(ex.map(job, cands))
+
+
+def pick(cands, results, quota_by_group):
+    """Primaries first in order; failures replaced by the group's backups in order."""
+    chosen, rejects = [], []
+    for g, quota in quota_by_group.items():
+        items = [(c, r) for c, r in zip(cands, results) if c["group"] == g]
+        prim = [x for x in items if x[0]["rank"] == "primary"]
+        back = [x for x in items if x[0]["rank"] == "backup"]
+        got = []
+        for c, r in prim + back:
+            if len(got) >= quota:
+                break
+            if r[1]:
+                got.append((c, r[0]))
+            elif c["rank"] == "primary":
+                rejects.append((c, r[2]))
+        if len(got) < quota:
+            print(f"!! group {g}: only {len(got)}/{quota}")
+        chosen += got
+    return chosen, rejects
+
+
+def main():
+    cities = json.load(open(os.path.join(HERE, "city_candidates.json")))
+    for c in cities:
+        c["kind"], c["group"] = "city", "c:" + c["region"]
+        if c["name"] in CITY_OVERRIDES:
+            c["lat"], c["lon"] = CITY_OVERRIDES[c["name"]]
+    cquota = {}
+    for c in cities:
+        if c["rank"] == "primary":
+            cquota[c["group"]] = cquota.get(c["group"], 0) + 1
+    assert sum(cquota.values()) == N_CITIES, cquota
+
+    lms = [dict(name=n, country=co, lat=la, lon=lo, zoom=z, kind="landmark", group="landmark",
+                rank="backup" if n in LANDMARK_BACKUPS else "primary") for n, co, la, lo, z in LANDMARKS]
+    lms.sort(key=lambda c: c["rank"] != "primary")  # stable: primaries first
+    nprim = sum(c["rank"] == "primary" for c in lms)
+    assert nprim == N_LANDMARKS, nprim
+
+    allc = cities + lms
+    print(f"evaluating {len(allc)} candidates ...", flush=True)
+    res = evaluate(allc)
+    quotas = dict(cquota)
+    quotas["landmark"] = N_LANDMARKS
+    chosen, rejects = pick(allc, res, quotas)
+
+    chosen.sort(key=lambda x: x[0]["lon"])
+    os.makedirs(OUT, exist_ok=True)
+    for f in glob.glob(os.path.join(OUT, "fx_*.jpg")):
+        os.remove(f)
+    index = []
+    for i, (c, img) in enumerate(chosen):
+        fn = f"fx_{i:03d}.jpg"
+        img.save(os.path.join(OUT, fn), quality=86, optimize=True)
+        index.append({"file": fn, "name": c["name"], "country": c["country"], "lat": round(c["lat"], 5),
+                      "lon": round(c["lon"], 5), "zoom": c["zoom"], "kind": c["kind"]})
+    with open(os.path.join(OUT, "index.json"), "w") as f:
+        json.dump(index, f, indent=1, ensure_ascii=False)
+
+    # contact sheet: 16 x 17 grid of 96px thumbs, west->east reading order
+    cols, cell = 16, 96
+    rows = (len(chosen) + cols - 1) // cols
+    sheet = Image.new("RGB", (cols * cell, rows * cell), (10, 10, 10))
+    for i, (c, img) in enumerate(chosen):
+        sheet.paste(img.resize((cell, cell), Image.LANCZOS), ((i % cols) * cell, (i // cols) * cell))
+    sheet.save(os.path.join(HERE, "sheet.jpg"), quality=88)
+
+    from collections import Counter
+    print(f"wrote {len(index)} captures: {Counter(x['kind'] for x in index)}")
+    print("rejected primaries (replaced by backups):")
+    for c, why in rejects:
+        print(f"  - {c['name']} ({c['country']}): {why}")
+    bands = Counter(int((x["lon"] + 180) // 30) for x in index)
+    print("30-degree longitude bands W->E:", [bands.get(i, 0) for i in range(12)])
+    json.dump([{"name": c["name"], "country": c["country"], "reason": why} for c, why in rejects],
+              open(os.path.join(HERE, "rejects.json"), "w"), indent=1, ensure_ascii=False)
+
+
+if __name__ == "__main__":
+    main()

intro-sequence/tools/flurry/landmarks.py

@@ -0,0 +1,205 @@
+"""Hand-picked non-city landmarks for the flurry montage.
+
+(name, country, lat, lon, zoom). zoom 16 for compact features, 15 for very large
+ones (deltas, glaciers, big pits, pivot fields). Coordinates are verified
+visually via tools/flurry/review.py sheets; entries that came back as featureless
+terrain were corrected or dropped (see REJECTED at the bottom).
+"""
+
+LANDMARKS = [
+    # --- ports / container terminals ---
+    ("Port of Rotterdam, Maasvlakte", "Netherlands", 51.9575, 4.0500, 16),
+    ("Port of Singapore, Pasir Panjang", "Singapore", 1.2735, 103.7750, 16),
+    ("Yangshan Deep-Water Port", "China", 30.6280, 122.0650, 16),
+    ("Port of Los Angeles, Pier 400", "United States of America", 33.7350, -118.2550, 16),
+    ("Jebel Ali Port", "United Arab Emirates", 25.0100, 55.0600, 16),
+    ("Port of Santos", "Brazil", -23.9700, -46.3000, 16),
+    ("Port of Hamburg, Burchardkai", "Germany", 53.5350, 9.9200, 16),
+    ("Port Hedland salt ponds", "Australia", -20.3450, 118.6550, 15),
+    ("Busan New Port", "South Korea", 35.0800, 128.8000, 16),
+    ("Tanger Med Port", "Morocco", 35.8850, -5.5000, 16),
+    ("Port of Tema", "Ghana", 5.6330, 0.0100, 16),
+    # --- airports ---
+    ("Hartsfield-Jackson Atlanta Airport", "United States of America", 33.6407, -84.4277, 16),
+    ("Dubai International Airport", "United Arab Emirates", 25.2528, 55.3644, 16),
+    ("Hong Kong International Airport", "Hong Kong S.A.R.", 22.3080, 113.9185, 16),
+    ("Denver International Airport", "United States of America", 39.8494, -104.6738, 16),
+    ("Kansai International Airport", "Japan", 34.4320, 135.2304, 16),
+    ("Beijing Daxing Airport", "China", 39.5098, 116.4105, 16),
+    ("Davis-Monthan Aircraft Boneyard", "United States of America", 32.1500, -110.8300, 16),
+    ("Princess Juliana Airport", "Sint Maarten", 18.0410, -63.1089, 16),
+    ("Gibraltar Airport runway", "Gibraltar", 36.1512, -5.3497, 16),
+    ("Faa'a International Airport", "French Polynesia", -17.5537, -149.6067, 16),
+    ("Funafuti Airfield", "Tuvalu", -8.5250, 179.1960, 16),
+    ("Midway Atoll, Sand Island", "United States of America", 28.2100, -177.3800, 16),
+    ("Wake Island Airfield", "United States of America", 19.2820, 166.6470, 16),
+    # --- dams ---
+    ("Hoover Dam", "United States of America", 36.0160, -114.7377, 16),
+    ("Three Gorges Dam", "China", 30.8233, 111.0036, 16),
+    ("Itaipu Dam", "Brazil", -25.4085, -54.5888, 16),
+    ("Grand Coulee Dam", "United States of America", 47.9560, -118.9817, 16),
+    ("Kariba Dam", "Zimbabwe", -16.5222, 28.7614, 16),
+    ("Aswan High Dam", "Egypt", 23.9707, 32.8780, 16),
+    ("Grand Ethiopian Renaissance Dam", "Ethiopia", 11.2150, 35.0900, 16),
+    ("Glen Canyon Dam", "United States of America", 36.9375, -111.4844, 16),
+    ("Akosombo Dam", "Ghana", 6.2999, 0.0592, 16),
+    ("Inga Dams", "Congo (Kinshasa)", -5.5240, 13.6200, 16),
+    # --- open-pit mines ---
+    ("Bingham Canyon Mine", "United States of America", 40.5230, -112.1510, 15),
+    ("Chuquicamata Mine", "Chile", -22.2900, -68.9000, 15),
+    ("Mir Diamond Mine", "Russia", 62.5275, 113.9936, 15),
+    ("Escondida Mine", "Chile", -24.2700, -69.0700, 15),
+    ("Kalgoorlie Super Pit", "Australia", -30.7775, 121.5040, 15),
+    ("Udachnaya Pipe", "Russia", 66.4300, 112.3200, 15),
+    ("Garzweiler Lignite Mine", "Germany", 51.0600, 6.4800, 15),
+    ("Kimberley Big Hole", "South Africa", -28.7383, 24.7585, 16),
+    ("Diavik Diamond Mine", "Canada", 64.4960, -110.2700, 15),
+    ("Syncrude Mildred Lake oil sands", "Canada", 57.0400, -111.6000, 15),
+    # --- solar ---
+    ("Noor Ouarzazate Solar", "Morocco", 31.0498, -6.8686, 16),
+    ("Ivanpah Solar", "United States of America", 35.5525, -115.4680, 16),
+    ("Crescent Dunes Solar", "United States of America", 38.2386, -117.3636, 15),
+    ("Bhadla Solar Park", "India", 27.5400, 71.9100, 16),
+    ("Gemasolar", "Spain", 37.5606, -5.3317, 16),
+    ("PS10 / PS20 Solar Towers", "Spain", 37.4425, -6.2550, 16),
+    ("Benban Solar Park", "Egypt", 24.4500, 32.7300, 16),
+    ("Cerro Dominador Solar", "Chile", -22.7700, -69.4800, 16),
+    # --- centre-pivot irrigation ---
+    ("Centre-pivot fields, Kansas", "United States of America", 37.9000, -100.9000, 15),
+    ("Centre-pivot fields, Wadi As-Sirhan", "Saudi Arabia", 30.2000, 38.0800, 15),
+    ("Kufra agricultural project", "Libya", 24.1400, 23.3500, 15),
+    ("East Oweinat pivots", "Egypt", 22.6000, 28.6000, 15),
+    ("Centre-pivot fields, Nebraska", "United States of America", 41.1000, -101.7000, 15),
+    # --- river deltas / water ---
+    ("Lena Delta", "Russia", 72.8000, 126.5000, 15),
+    ("Okavango Delta", "Botswana", -19.3000, 22.9000, 15),
+    ("Betsiboka Estuary", "Madagascar", -15.7500, 46.3500, 15),
+    ("Meeting of the Waters, Manaus", "Brazil", -3.1370, -59.9100, 15),
+    # --- salt / evaporation ---
+    ("Salar de Atacama lithium ponds", "Chile", -23.5280, -68.3680, 16),
+    ("Dead Sea evaporation ponds", "Israel", 31.1000, 35.4000, 15),
+    ("San Francisco Bay salt ponds", "United States of America", 37.5000, -122.0500, 15),
+    ("Lake Retba (Pink Lake)", "Senegal", 14.8400, -17.2300, 15),
+    ("Hutt Lagoon", "Australia", -28.1700, 114.2500, 15),
+    # --- glaciers / ice ---
+    ("Perito Moreno Glacier", "Argentina", -50.4800, -73.0500, 15),
+    ("Aletsch Glacier, Konkordiaplatz", "Switzerland", 46.5000, 8.0300, 15),
+    ("Hubbard Glacier", "United States of America", 60.0200, -139.5000, 15),
+    # Antarctica: Esri has only Landsat-class imagery here (z14+ is placeholder),
+    # so these use z11-12 where the source pixels are native rather than upsampled.
+    ("Taylor Valley, Canada Glacier", "Antarctica", -77.6300, 162.9500, 12),
+    ("McMurdo Dry Valleys, Wright Valley", "Antarctica", -77.5700, 161.8500, 11),
+    ("Deception Island caldera", "Antarctica", -62.9600, -60.6300, 12),
+    ("Mount Everest", "Nepal", 27.9881, 86.9250, 15),
+    # --- volcanoes / craters ---
+    ("Mount Bromo", "Indonesia", -7.9420, 112.9530, 15),
+    ("Erta Ale", "Ethiopia", 13.6065, 40.6655, 16),
+    ("Kilauea, Halemaumau", "United States of America", 19.4060, -155.2830, 15),
+    ("Mount Fuji summit crater", "Japan", 35.3628, 138.7307, 16),
+    ("Nyiragongo", "Congo (Kinshasa)", -1.5200, 29.2500, 16),
+    ("Meteor Crater", "United States of America", 35.0275, -111.0225, 15),
+    ("Mount St. Helens", "United States of America", 46.2000, -122.1900, 15),
+    ("Kawah Ijen", "Indonesia", -8.0580, 114.2420, 16),
+    ("Teide", "Spain", 28.2725, -16.6425, 16),
+    ("Mount Vesuvius", "Italy", 40.8216, 14.4263, 16),
+    ("Rano Kau, Easter Island", "Chile", -27.1860, -109.4350, 15),
+    ("Diamond Head", "United States of America", 21.2620, -157.8050, 15),
+    ("Darvaza Gas Crater", "Turkmenistan", 40.2525, 58.4394, 16),
+    ("Kilimanjaro, Kibo crater", "Tanzania", -3.0758, 37.3533, 15),
+    ("Mount Taranaki", "New Zealand", -39.2968, 174.0634, 15),
+    ("Whakaari / White Island", "New Zealand", -37.5200, 177.1800, 15),
+    ("Dallol", "Ethiopia", 14.2400, 40.3000, 16),
+    # --- stadiums / venues ---
+    ("Maracana Stadium", "Brazil", -22.9122, -43.2302, 16),
+    ("Rungrado May Day Stadium", "North Korea", 39.0497, 125.7756, 16),
+    ("Camp Nou", "Spain", 41.3809, 2.1228, 16),
+    ("Beijing National Stadium", "China", 39.9925, 116.3910, 16),
+    ("Melbourne Cricket Ground", "Australia", -37.8200, 144.9834, 16),
+    ("Indianapolis Motor Speedway", "United States of America", 39.7950, -86.2350, 15),
+    ("Estadio Azteca", "Mexico", 19.3029, -99.1505, 16),
+    ("FNB Stadium, Soweto", "South Africa", -26.2348, 27.9825, 16),
+    # --- bridges / canals ---
+    ("Golden Gate Bridge", "United States of America", 37.8100, -122.4770, 16),
+    ("Sydney Harbour Bridge & Opera House", "Australia", -33.8550, 151.2120, 16),
+    ("Tower Bridge", "United Kingdom", 51.5055, -0.0754, 16),
+    ("Oresund Bridge, Peberholm", "Denmark", 55.5900, 12.7740, 16),
+    ("Millau Viaduct", "France", 44.0794, 3.0225, 16),
+    ("Brooklyn Bridge", "United States of America", 40.7061, -73.9969, 16),
+    ("Panama Canal, Miraflores Locks", "Panama", 8.9970, -79.5915, 16),
+    ("Panama Canal, Agua Clara Locks", "Panama", 9.2720, -79.9180, 16),
+    # --- launch sites ---
+    ("Kennedy Space Center LC-39A", "United States of America", 28.6083, -80.6041, 16),
+    ("Baikonur, Gagarin's Start", "Kazakhstan", 45.9203, 63.3422, 16),
+    ("Vandenberg SLC-4E", "United States of America", 34.6320, -120.6110, 16),
+    ("Starbase, Boca Chica", "United States of America", 25.9972, -97.1566, 16),
+    ("Wenchang Launch Site", "China", 19.6145, 110.9510, 16),
+    ("Jiuquan Launch Centre", "China", 40.9580, 100.2910, 16),
+    ("Tanegashima Space Center", "Japan", 30.4009, 130.9749, 16),
+    ("Vostochny Cosmodrome", "Russia", 51.8840, 128.3330, 16),
+    ("Rocket Lab LC-1, Mahia", "New Zealand", -39.2615, 177.8649, 16),
+    # --- energy / industry ---
+    ("Permian Basin well pads", "United States of America", 32.2100, -103.8300, 15),
+    ("Ras Tanura refinery", "Saudi Arabia", 26.6400, 50.1600, 16),
+    ("Jamnagar Refinery", "India", 22.3500, 69.8500, 16),
+    ("Ras Laffan Industrial City", "Qatar", 25.9100, 51.5500, 16),
+    ("Yamal LNG, Sabetta", "Russia", 71.2700, 72.0700, 16),
+    ("Chernobyl Nuclear Power Plant", "Ukraine", 51.3890, 30.0990, 16),
+    # --- monuments / sites ---
+    ("Jiayuguan Pass, Great Wall", "China", 39.8016, 98.2133, 16),
+    ("Pyramids of Giza", "Egypt", 29.9792, 31.1342, 16),
+    ("Palm Jumeirah", "United Arab Emirates", 25.1124, 55.1390, 15),
+    ("Angkor Wat", "Cambodia", 13.4125, 103.8670, 16),
+    ("The Pentagon", "United States of America", 38.8719, -77.0563, 16),
+    ("Groom Lake", "United States of America", 37.2350, -115.8111, 15),
+    ("FAST Radio Telescope", "China", 25.6529, 106.8566, 16),
+    ("Very Large Array", "United States of America", 34.0784, -107.6184, 16),
+    ("Uluru", "Australia", -25.3444, 131.0369, 15),
+    ("Mont-Saint-Michel", "France", 48.6361, -1.5115, 16),
+    ("Grand Prismatic Spring", "United States of America", 44.5251, -110.8382, 16),
+    ("Masjid al-Haram, Mecca", "Saudi Arabia", 21.4225, 39.8262, 16),
+    ("Forbidden City", "China", 39.9155, 116.3910, 16),
+    ("Taj Mahal", "India", 27.1751, 78.0421, 16),
+    ("Greenhouses of Almeria", "Spain", 36.7500, -2.7200, 16),
+    ("Pine Gap", "Australia", -23.7990, 133.7370, 16),
+    ("ALMA Observatory", "Chile", -23.0229, -67.7552, 16),
+    ("Paranal Observatory", "Chile", -24.6275, -70.4044, 16),
+    ("Brasilia, National Congress", "Brazil", -15.7998, -47.8645, 16),
+    ("Iguazu Falls, Devil's Throat", "Argentina", -25.6950, -54.4367, 16),
+    ("Niagara Horseshoe Falls", "Canada", 43.0773, -79.0757, 16),
+    ("Victoria Falls", "Zambia", -17.9243, 25.8572, 16),
+    ("Horseshoe Bend", "United States of America", 36.8791, -111.5103, 16),
+    ("Sossusvlei dunes", "Namibia", -24.7300, 15.2900, 15),
+    ("Erg Chebbi dunes", "Morocco", 31.1500, -3.9800, 15),
+    ("Bora Bora", "French Polynesia", -16.4950, -151.7050, 15),
+    ("Borobudur", "Indonesia", -7.6079, 110.2038, 16),
+    ("Bagan temples", "Myanmar", 21.1700, 94.8600, 16),
+    ("Svalbard, Longyearbyen", "Norway", 78.2200, 15.6500, 16),
+    ("Edinburgh of the Seven Seas, Tristan da Cunha", "United Kingdom", -37.0670, -12.3100, 16),
+    ("Diego Garcia", "United Kingdom", -7.3100, 72.4100, 15),
+    ("Kwajalein Atoll", "Marshall Islands", 8.7200, 167.7300, 16),
+]
+
+REJECTED = {
+    'Pituffik Space Base': 'placeholder above z13; z13 too blurry',
+    'Ilulissat Icefjord': 'placeholder above z13; open water at z13',
+    'McMurdo Station': 'placeholder above z13; blurry ice at z13',
+    'Rothera Research Station': 'placeholder above z13; mostly sea',
+    'Mount Erebus crater': 'placeholder above z13; cloud-like blur',
+    'Port of Durban': "featureless/cloud/low-res/off-target at tested coords",
+    'Port of Mombasa': "featureless/cloud/low-res/off-target at tested coords",
+    'Sundarbans, Ganges Delta': "featureless/cloud/low-res/off-target at tested coords",
+    "Mississippi Bird's-Foot Delta": "featureless/cloud/low-res/off-target at tested coords",
+    'Volga Delta': "featureless/cloud/low-res/off-target at tested coords",
+    'Great Salt Lake causeway': "featureless/cloud/low-res/off-target at tested coords",
+    'Jokulsarlon Glacier Lagoon': "featureless/cloud/low-res/off-target at tested coords",
+    'Baltoro Glacier, Concordia': "featureless/cloud/low-res/off-target at tested coords",
+    'Cotopaxi': "featureless/cloud/low-res/off-target at tested coords",
+    'Guiana Space Centre ELA-3': "featureless/cloud/low-res/off-target at tested coords",
+    'Satish Dhawan Space Centre': "featureless/cloud/low-res/off-target at tested coords",
+    'Abqaiq processing plant': "featureless/cloud/low-res/off-target at tested coords",
+    'Prudhoe Bay oil field': "featureless/cloud/low-res/off-target at tested coords",
+    'Great Wall at Mutianyu': "featureless/cloud/low-res/off-target at tested coords",
+    'Machu Picchu': "featureless/cloud/low-res/off-target at tested coords",
+    'Baltra Island airport, Galapagos': "featureless/cloud/low-res/off-target at tested coords",
+    'Moynaq ship graveyard, Aral Sea': "featureless/cloud/low-res/off-target at tested coords",
+}

intro-sequence/tools/flurry/locate.py

@@ -0,0 +1,78 @@
+"""Locator sheets: a wider mosaic around a guess with a lat/lon grid, to find exact coords.
+
+usage: python3 locate.py out.jpg "name|lat|lon|z|ntiles" ...
+Each panel is ntiles x ntiles tiles at zoom z (resized to 640px) with grid
+lines every `step` degrees, labelled. Panels are stacked in a 2-column grid.
+"""
+import io
+import math
+import os
+import sys
+from concurrent.futures import ThreadPoolExecutor
+
+from PIL import Image, ImageDraw
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from tiles import fetch_tile, pixel_xy  # noqa: E402
+
+P = 640
+
+
+def panel(name, lat, lon, z, nt):
+    px, py = pixel_xy(lat, lon, z)
+    tx, ty = int(px // 256), int(py // 256)
+    h = nt // 2
+    coords = [(tx - h + i, ty - h + j) for j in range(nt) for i in range(nt)]
+    with ThreadPoolExecutor(8) as ex:
+        datas = list(ex.map(lambda c: fetch_tile(z, c[0], c[1]), coords))
+    m = Image.new("RGB", (nt * 256, nt * 256))
+    for (x, y), d in zip(coords, datas):
+        m.paste(Image.open(io.BytesIO(d)).convert("RGB"), ((x - tx + h) * 256, (y - ty + h) * 256))
+    ox, oy = (tx - h) * 256, (ty - h) * 256
+    s = P / (nt * 256)
+    m = m.resize((P, P), Image.LANCZOS)
+    d = ImageDraw.Draw(m)
+    n = 2 ** z * 256
+
+    def lon2x(lo):
+        return ((lo + 180) / 360 * n - ox) * s
+
+    def lat2y(la):
+        si = math.sin(math.radians(la))
+        return ((0.5 - math.log((1 + si) / (1 - si)) / (4 * math.pi)) * n - oy) * s
+
+    span = nt * 256 / n * 360
+    step = [0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5][
+        min(range(9), key=lambda k: abs(span / [0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5][k] - 6))]
+    lo0 = math.floor((lon - span) / step) * step
+    for k in range(40):
+        lo = lo0 + k * step
+        x = lon2x(lo)
+        if 0 <= x <= P:
+            d.line((x, 0, x, P), fill=(255, 255, 0), width=1)
+            d.text((x + 2, P - 12), f"{lo:.3f}", fill=(255, 255, 0))
+    la0 = math.floor((lat - span) / step) * step
+    for k in range(40):
+        la = la0 + k * step
+        y = lat2y(la)
+        if 0 <= y <= P:
+            d.line((0, y, P, y), fill=(0, 255, 255), width=1)
+            d.text((2, y + 1), f"{la:.3f}", fill=(0, 255, 255))
+    cx, cy = lon2x(lon), lat2y(lat)
+    d.ellipse((cx - 5, cy - 5, cx + 5, cy + 5), outline=(255, 0, 0), width=2)
+    d.rectangle((0, 0, P, 14), fill=(0, 0, 0))
+    d.text((3, 1), f"{name} z{z}", fill=(255, 255, 255))
+    return m
+
+
+if __name__ == "__main__":
+    out = sys.argv[1]
+    specs = [a.split("|") for a in sys.argv[2:]]
+    ps = [panel(s[0], float(s[1]), float(s[2]), int(s[3]), int(s[4])) for s in specs]
+    cols = 2 if len(ps) > 1 else 1
+    rows = (len(ps) + cols - 1) // cols
+    sheet = Image.new("RGB", (cols * P, rows * P))
+    for i, p in enumerate(ps):
+        sheet.paste(p, ((i % cols) * P, (i // cols) * P))
+    sheet.save(out, quality=85)
+    print(out)

intro-sequence/tools/flurry/rejects.json

@@ -0,0 +1,32 @@
+[
+ {
+  "name": "Venice",
+  "country": "Italy",
+  "reason": "visual: blurry low-res imagery"
+ },
+ {
+  "name": "Chengdu",
+  "country": "China",
+  "reason": "visual: smog haze"
+ },
+ {
+  "name": "Xian",
+  "country": "China",
+  "reason": "visual: washed-out industrial lot"
+ },
+ {
+  "name": "Maracaibo",
+  "country": "Venezuela",
+  "reason": "visual: farmland / scrub"
+ },
+ {
+  "name": "Barquisimeto",
+  "country": "Venezuela",
+  "reason": "visual: dry riverbed, no city"
+ },
+ {
+  "name": "Conakry",
+  "country": "Guinea",
+  "reason": "visual: heavy haze"
+ }
+]

intro-sequence/tools/flurry/review.py

@@ -0,0 +1,69 @@
+"""Fetch candidates and render labelled review sheets for visual verification.
+
+usage: python3 review.py landmarks|cities [start] [count]
+Writes tools/flurry/review/<kind>_NN.jpg (5x4 grid, 256px cells, labelled).
+"""
+import json
+import os
+import sys
+from concurrent.futures import ThreadPoolExecutor
+
+from PIL import Image, ImageDraw
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from tiles import HERE, MAX_WORKERS, capture, quality_ok  # noqa: E402
+
+REV = os.path.join(HERE, "review")
+
+
+def load(kind):
+    if kind == "landmarks":
+        from landmarks import LANDMARKS
+        return [dict(name=n, country=c, lat=la, lon=lo, zoom=z) for n, c, la, lo, z in LANDMARKS]
+    return json.load(open(os.path.join(HERE, "city_candidates.json")))
+
+
+def run(cands, prefix, cell=256, cols=5, rows=4):
+    os.makedirs(REV, exist_ok=True)
+
+    def job(c):
+        try:
+            img, info = capture(c["lat"], c["lon"], c["zoom"])
+            return img, info
+        except Exception as e:
+            return None, {"error": str(e)}
+
+    with ThreadPoolExecutor(MAX_WORKERS) as ex:
+        res = list(ex.map(job, cands))
+    per = cols * rows
+    report = []
+    for s in range(0, len(cands), per):
+        sheet = Image.new("RGB", (cols * cell, rows * cell), (20, 20, 20))
+        d = ImageDraw.Draw(sheet)
+        for k, (c, (img, info)) in enumerate(zip(cands[s:s + per], res[s:s + per])):
+            x, y = (k % cols) * cell, (k // cols) * cell
+            idx = s + k
+            if img is not None:
+                sheet.paste(img.resize((cell, cell), Image.LANCZOS), (x, y))
+                ok, why = quality_ok(info)
+                lab2 = f"s{info['std']:.0f} g{info['grad']:.1f}" + ("" if ok else " X " + why[:18])
+            else:
+                ok, lab2 = False, "ERR"
+            d.rectangle((x, y, x + cell, y + 24), fill=(0, 0, 0))
+            d.text((x + 3, y + 1), f"{idx} {c['name'][:36]}", fill=(255, 255, 0))
+            d.text((x + 3, y + 12), lab2, fill=(255, 120, 120) if not ok else (160, 255, 160))
+            report.append((idx, c["name"], ok, lab2))
+        out = os.path.join(REV, f"{prefix}_{s // per:02d}.jpg")
+        sheet.save(out, quality=85)
+        print(out)
+    for r in report:
+        if not r[2]:
+            print("REJECT", r)
+
+
+if __name__ == "__main__":
+    kind = sys.argv[1]
+    cands = load(kind)
+    st = int(sys.argv[2]) if len(sys.argv) > 2 else 0
+    n = int(sys.argv[3]) if len(sys.argv) > 3 else len(cands)
+    run(cands[st:st + n], kind[:2] + (f"_{st}" if st else ""))

intro-sequence/tools/flurry/select_cities.py

@@ -0,0 +1,109 @@
+"""Pick ~170 city centres from data/cities.json with geographic spread.
+
+Writes tools/flurry/city_candidates.json: ordered list of dicts with
+rank ("primary"/"backup") and region. Backups replace rejected primaries of the
+same region in build.py.
+"""
+import json
+import math
+import os
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+ROOT = os.path.abspath(os.path.join(HERE, "..", ".."))
+
+AFRICA = {
+    "Nigeria", "Egypt", "Congo (Kinshasa)", "South Africa", "Algeria", "Sudan", "Morocco", "Tanzania",
+    "Cameroon", "Mozambique", "Libya", "Ethiopia", "Ivory Coast", "Tunisia", "Zambia", "Angola", "Ghana",
+    "Uganda", "Kenya", "Guinea", "Madagascar", "Senegal", "Zimbabwe", "Mali", "Somalia", "Chad", "Niger",
+    "Benin", "Eritrea", "Somaliland", "South Sudan", "Sierra Leone", "Mauritania", "Malawi", "Togo",
+    "Congo (Brazzaville)", "Burkina Faso", "Rwanda", "Mauritius", "Gabon", "Equatorial Guinea", "Liberia",
+    "Djibouti", "Central African Republic", "Guinea Bissau", "Lesotho", "Burundi", "Namibia", "Botswana",
+    "The Gambia", "Comoros", "Cape Verde", "eSwatini",
+}
+SOUTH_AMERICA = {"Brazil", "Argentina", "Colombia", "Venezuela", "Peru", "Chile", "Ecuador", "Bolivia",
+                 "Paraguay", "Uruguay", "Guyana", "Suriname"}
+OCEANIA = {"Australia", "New Zealand", "Papua New Guinea", "Fiji", "French Polynesia", "Guam"}
+CENTRAL_ASIA = {"Kazakhstan", "Uzbekistan", "Turkmenistan", "Kyrgyzstan", "Tajikistan", "Afghanistan", "Mongolia"}
+
+# (region, primary quota, backups, per-country cap, min spacing km)
+PASSES = [
+    ("africa", AFRICA, 31, 16, 3, 300),
+    ("south_america", SOUTH_AMERICA, 22, 10, 5, 250),
+    ("oceania", OCEANIA, 12, 4, 5, 120),
+    ("central_asia", CENTRAL_ASIA, 9, 5, 3, 150),
+    ("rest", None, 96, 40, 11, 200),
+]
+# Picked first (in "rest" unless their country is in a quota region): fill the
+# Pacific / high-latitude longitude bands and add visually distinctive cities.
+FORCED = [
+    "Honolulu", "Anchorage", "Papeete", "Agana", "Petropavlovsk-Kamchatsky", "Vancouver", "San Francisco",
+    "Las Vegas", "Seattle", "Phoenix", "Denver", "Calgary", "Guatemala City", "Havana", "Reykjavík",
+    "Dubai", "Doha", "Abu Dhabi", "Hong Kong", "Macau", "Venice", "Amsterdam", "København", "Oslo",
+    "Stockholm", "Helsinki", "Prague", "Kathmandu", "Colombo", "Vladivostok", "Novosibirsk", "Irkutsk",
+    "Yakutsk", "Norilsk", "Murmansk", "Manaus", "Mombasa", "Windhoek", "Nouakchott", "Marrakesh",
+    "Samarkand", "Cairns", "Muscat", "Québec",
+]
+# Natural Earth rows whose point lands in farmland/hills rather than a dense centre.
+EXCLUDE = {"Amaravati", "Hechi", "Saidu", "Cranbourne", "Manukau", "Waitakere", "North Shore", "Wahiawa"}
+COUNTRY_CAP_TOTAL = 12
+
+
+def km(a, b):
+    la1, lo1, la2, lo2 = map(math.radians, (a[1], a[0], b[1], b[0]))
+    h = math.sin((la2 - la1) / 2) ** 2 + math.cos(la1) * math.cos(la2) * math.sin((lo2 - lo1) / 2) ** 2
+    return 6371 * 2 * math.asin(math.sqrt(h))
+
+
+def main():
+    rows = json.load(open(os.path.join(ROOT, "data", "cities.json")))["rows"]
+    special = AFRICA | SOUTH_AMERICA | OCEANIA | CENTRAL_ASIA
+    chosen, out = [], []
+    byname = {}
+    for r in rows:
+        byname.setdefault(r[3], r)  # first = most populous
+    per = {}
+
+    def region_of(country):
+        for reg, mem, *_ in PASSES:
+            if mem and country in mem:
+                return reg
+        return "rest"
+
+    for nm in FORCED:
+        lon, lat, pop, name, country = byname[nm]
+        chosen.append((lon, lat))
+        per[country] = per.get(country, 0) + 1
+        out.append(dict(name=name, country=country, lat=lat, lon=lon, zoom=16, pop=pop,
+                        region=region_of(country), rank="primary", forced=True))
+    for region, members, quota, nback, cap, spacing in PASSES:
+        got = sum(1 for c in out if c["region"] == region)
+        for lon, lat, pop, name, country in rows:
+            if name in EXCLUDE or name in byname and any(c["name"] == name and c["country"] == country for c in out):
+                continue
+            inreg = (country in members) if members else (country not in special)
+            if not inreg:
+                continue
+            if per.get(country, 0) >= cap and got < quota or per.get(country, 0) >= COUNTRY_CAP_TOTAL:
+                continue
+            if any(km((lon, lat), (c[0], c[1])) < spacing for c in chosen):
+                continue
+            rank = "primary" if got < quota else "backup"
+            chosen.append((lon, lat))
+            per[country] = per.get(country, 0) + 1
+            out.append(dict(name=name, country=country, lat=lat, lon=lon, zoom=16, pop=pop,
+                            region=region, rank=rank))
+            got += 1
+            if got >= quota + nback:
+                break
+    json.dump(out, open(os.path.join(HERE, "city_candidates.json"), "w"), indent=0, ensure_ascii=False)
+    prim = [c for c in out if c["rank"] == "primary"]
+    print(len(prim), "primary,", len(out) - len(prim), "backup")
+    from collections import Counter
+    print(Counter(c["region"] for c in prim))
+    print(Counter(c["country"] for c in prim).most_common(12))
+    bands = Counter(int((c["lon"] + 180) // 30) for c in prim)
+    print("30deg bands:", [bands.get(i, 0) for i in range(12)])
+
+
+if __name__ == "__main__":
+    main()

intro-sequence/tools/flurry/tiles.py

@@ -0,0 +1,132 @@
+"""Polite cached Esri World Imagery fetch + 512px centred capture + quality metrics."""
+import hashlib
+import io
+import math
+import os
+import threading
+import time
+
+import numpy as np
+import requests
+from PIL import Image
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+CACHE = os.path.join(HERE, "cache")
+ROOT = os.path.abspath(os.path.join(HERE, "..", ".."))
+OUT = os.path.join(ROOT, "imagery", "flurry")
+
+ESRI = "https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}"
+UA = "gods-eye-view-intro/1.0 (flurry montage prep)"
+MAX_WORKERS = 8
+PLACEHOLDER_MD5 = {"f27d9de7f80c13501f470595e327aa6d"}  # "Map data not yet available"
+
+_local = threading.local()
+
+
+def _session():
+    s = getattr(_local, "s", None)
+    if s is None:
+        s = requests.Session()
+        s.headers["User-Agent"] = UA
+        _local.s = s
+    return s
+
+
+def fetch_tile(z, x, y, retries=6):
+    n = 2 ** z
+    x %= n
+    path = os.path.join(CACHE, str(z), str(x), f"{y}.jpg")
+    if os.path.exists(path) and os.path.getsize(path) > 0:
+        with open(path, "rb") as f:
+            return f.read()
+    os.makedirs(os.path.dirname(path), exist_ok=True)
+    url = ESRI.format(z=z, x=x, y=y)
+    last = None
+    for attempt in range(retries):
+        try:
+            r = _session().get(url, timeout=45)
+            if r.status_code == 200 and r.content:
+                tmp = path + f".{threading.get_ident()}.part"
+                with open(tmp, "wb") as f:
+                    f.write(r.content)
+                os.replace(tmp, path)
+                return r.content
+            last = f"HTTP {r.status_code}"
+            if r.status_code in (400, 404):
+                break
+        except Exception as e:
+            last = repr(e)
+        time.sleep(min(20, 1.0 * 2 ** attempt))
+    raise RuntimeError(f"failed {url}: {last}")
+
+
+def is_placeholder(data):
+    if hashlib.md5(data).hexdigest() in PLACEHOLDER_MD5:
+        return True
+    a = np.asarray(Image.open(io.BytesIO(data)).convert("RGB")).astype(np.float32)
+    m = a.mean(axis=(0, 1))
+    return bool(abs(m - 204.7).max() < 4 and a.std() < 9)
+
+
+def pixel_xy(lat, lon, z):
+    n = 2 ** z * 256
+    px = (lon + 180.0) / 360.0 * n
+    s = math.sin(math.radians(lat))
+    py = (0.5 - math.log((1 + s) / (1 - s)) / (4 * math.pi)) * n
+    return px, py
+
+
+def capture(lat, lon, z, size=512):
+    """Return (image, info). info has placeholder flag and quality metrics."""
+    px, py = pixel_xy(lat, lon, z)
+    tx, ty = int(px // 256), int(py // 256)
+    mosaic = Image.new("RGB", (768, 768))
+    ox, oy = (tx - 1) * 256, (ty - 1) * 256
+    left, top = int(round(px - ox - size / 2)), int(round(py - oy - size / 2))
+    ph = False
+    for j in range(3):
+        for i in range(3):
+            data = fetch_tile(z, tx - 1 + i, ty - 1 + j)
+            # does this tile overlap the crop window?
+            tl, tt = i * 256, j * 256
+            overlaps = tl < left + size and tl + 256 > left and tt < top + size and tt + 256 > top
+            if overlaps and is_placeholder(data):
+                ph = True
+            mosaic.paste(Image.open(io.BytesIO(data)).convert("RGB"), (tl, tt))
+    img = mosaic.crop((left, top, left + size, top + size))
+    info = metrics(img)
+    info["placeholder"] = ph
+    return img, info
+
+
+def metrics(img):
+    a = np.asarray(img).astype(np.float32)
+    lum = a @ np.array([0.299, 0.587, 0.114], np.float32)
+    small = np.asarray(img.convert("L").resize((128, 128), Image.BILINEAR)).astype(np.float32)
+    gx = np.abs(np.diff(lum, axis=1)).mean()
+    gy = np.abs(np.diff(lum, axis=0)).mean()
+    # coarse-scale structure: std of 32px block means (catches flat ocean/cloud/ice)
+    blocks = lum.reshape(16, 32, 16, 32).mean(axis=(1, 3))
+    sat = (a.max(axis=2) - a.min(axis=2)).mean()
+    return {
+        "std": float(lum.std()),
+        "grad": float((gx + gy) / 2),
+        "block_std": float(blocks.std()),
+        "small_std": float(small.std()),
+        "sat": float(sat),
+        "mean": float(lum.mean()),
+    }
+
+
+def quality_ok(info):
+    if info["placeholder"]:
+        return False, "placeholder"
+    if info["std"] < 12:
+        return False, f"low variance (std {info['std']:.1f})"
+    if info["grad"] < 1.3:
+        return False, f"featureless (grad {info['grad']:.1f})"
+    if info["mean"] > 225 and info["std"] < 25:
+        return False, "cloud/snow white-out"
+    if info["mean"] < 22:
+        return False, "too dark"
+    return True, ""

intro-sequence/tools/imagery/.gitignore

@@ -0,0 +1 @@
+cache/

intro-sequence/tools/imagery/build_clouds.py

@@ -0,0 +1,76 @@
+"""Deliverable 3: clouds.jpg (4096x2048) grayscale cloud opacity map for one recent day.
+
+Source: NASA GIBS daily VIIRS Corrected Reflectance True Colour for the same UTC
+date from three satellites (NOAA-20, NOAA-21, Suomi NPP), EPSG:4326 level 3
+(10x5 tiles of 512px = 5120x2560), downsampled to 4096x2048.
+
+Cloud metric per satellite:
+    whiteness = min(R,G,B)            (clouds are bright in every channel)
+    greyness  = 1 - saturation        (clouds are colourless)
+    c = ramp(whiteness) * smoothstep(greyness)
+The same metric computed on the Esri base map (earth_day_4k.jpg) is subtracted
+to suppress bright deserts, salt flats, snow and ice that would otherwise read
+as cloud. The three per-satellite results are combined with a per-pixel median
+(nan-aware), which removes swath-edge haze / glint streaks that only one
+satellite shows, and fills swath gaps. Remaining no-data (polar night) -> 0.
+
+Usage: python3 build_clouds.py [YYYY-MM-DD]
+"""
+import os
+import sys
+import numpy as np
+from PIL import Image
+from common import OUT, gibs_mosaic
+
+Image.MAX_IMAGE_PIXELS = None
+DATE = sys.argv[1] if len(sys.argv) > 1 else "2026-10-15"
+LAYERS = [
+    "VIIRS_NOAA20_CorrectedReflectance_TrueColor",
+    "VIIRS_NOAA21_CorrectedReflectance_TrueColor",
+    "VIIRS_SNPP_CorrectedReflectance_TrueColor",
+]
+W, H = 4096, 2048
+
+
+def smooth(x, a, b):
+    t = np.clip((x - a) / (b - a), 0, 1)
+    return t * t * (3 - 2 * t)
+
+
+def metric(rgb):
+    rgb = rgb.astype(np.float32) / 255.0
+    mn = rgb.min(2)
+    mx = rgb.max(2)
+    sat = (mx - mn) / (mx + 1e-4)
+    white = np.clip((mn - 0.14) / 0.86, 0, 1) ** 1.15  # linear-ish: keeps texture inside thick cloud
+    return white * smooth(1.0 - sat, 0.65, 0.95), mx
+
+
+def main():
+    base = np.asarray(Image.open(os.path.join(OUT, "earth_day_4k.jpg")).convert("RGB"))
+    base_c, _ = metric(base)
+    # dilate the base metric a few px so small Esri/VIIRS coastline misregistration
+    # does not leave bright outlines along desert and ice coasts
+    from PIL import ImageFilter
+    base_c = np.asarray(Image.fromarray((base_c * 255).astype(np.uint8)).filter(ImageFilter.MaxFilter(3)).filter(ImageFilter.GaussianBlur(2))).astype(np.float32) / 255
+    stack = []
+    for L in LAYERS:
+        m = gibs_mosaic(L, DATE, "250m", 3, 5, 10, "jpg").resize((W, H), Image.LANCZOS)
+        c, mx = metric(np.asarray(m))
+        c = np.clip(c - base_c * 1.1, 0, 1)
+        c[mx < 0.03] = np.nan  # no-data (black)
+        stack.append(c)
+    stack = np.stack(stack)
+    with np.errstate(all="ignore"):
+        import warnings
+        warnings.simplefilter("ignore")
+        cloud = np.nanmedian(stack, axis=0)
+    cloud = np.nan_to_num(cloud, nan=0.0)
+    cloud = np.clip((cloud - 0.06) / 0.94, 0, 1)  # black point: kill faint surface/haze residue
+    img = Image.fromarray(np.clip(cloud * 255 + 0.5, 0, 255).astype(np.uint8), "L")
+    img.save(os.path.join(OUT, "clouds.jpg"), quality=92, optimize=True, progressive=True)
+    print("done", DATE, "mean opacity %.3f" % cloud.mean())
+
+
+if __name__ == "__main__":
+    main()

intro-sequence/tools/imagery/build_day.py

@@ -0,0 +1,91 @@
+"""Deliverable 1: earth_day.jpg (8192x4096) + earth_day_4k.jpg (4096x2048).
+
+Esri World Imagery z5 (32x32 tiles, 8192x8192 Web Mercator) reprojected to
+equirectangular with bilinear sampling. Because both grids are 8192 px wide and
+linear in longitude, the horizontal axis maps 1:1 and only latitude needs
+resampling (linear interpolation between Mercator rows = bilinear).
+
+Polar caps beyond the Mercator limit (+-85.0511 deg) come from NASA GIBS
+BlueMarble_ShadedRelief_Bathymetry (EPSG:4326, level 4 = 10240x5120; its shaded
+bathymetry matches Esri's small-scale ocean rendering), colour-matched to Esri
+with a least-squares affine colour transform fitted on co-registered overlap pixels and cross-faded between 80 and 84.5 deg.
+"""
+import os
+import numpy as np
+from PIL import Image
+from common import OUT, esri_jobs, fetch_many, decode, gibs_mosaic
+
+Image.MAX_IMAGE_PIXELS = None
+W, H = 8192, 4096
+Z = 5
+N = 2 ** Z
+TS = 256
+MERC = N * TS  # 8192
+MERC_LIMIT = np.degrees(np.arctan(np.sinh(np.pi)))  # 85.0511
+FADE_A, FADE_B = 80.0, 84.5  # pure Esri below A, pure Blue Marble above B
+CAP_LAYER = os.environ.get("CAP_LAYER", "BlueMarble_ShadedRelief_Bathymetry")
+
+
+def esri_mercator():
+    coords = [(x, y) for y in range(N) for x in range(N)]
+    res = fetch_many(esri_jobs(Z, coords), desc="esri z5")
+    merc = np.zeros((MERC, MERC, 3), np.uint8)
+    for (x, y), b in res.items():
+        if b is None:
+            raise SystemExit(f"missing esri tile {x},{y}")
+        merc[y * TS:(y + 1) * TS, x * TS:(x + 1) * TS] = np.asarray(decode(b))
+    return merc
+
+
+def main():
+    merc = esri_mercator()
+    print("reprojecting")
+    lat = 90.0 - (np.arange(H) + 0.5) * 180.0 / H
+    latc = np.clip(lat, -MERC_LIMIT + 1e-6, MERC_LIMIT - 1e-6)
+    yn = (1.0 - np.log(np.tan(np.pi / 4 + np.radians(latc) / 2)) / np.pi) / 2.0
+    v = yn * MERC - 0.5
+    v0 = np.clip(np.floor(v).astype(int), 0, MERC - 1)
+    v1 = np.clip(v0 + 1, 0, MERC - 1)
+    f = np.clip(v - np.floor(v), 0, 1).astype(np.float32)[:, None, None]
+    eq = np.empty((H, W, 3), np.float32)
+    for s in range(0, H, 256):
+        e = s + 256
+        eq[s:e] = merc[v0[s:e]].astype(np.float32) * (1 - f[s:e]) + merc[v1[s:e]].astype(np.float32) * f[s:e]
+    del merc
+
+    print("fetching polar caps:", CAP_LAYER)
+    bm = gibs_mosaic(CAP_LAYER, None, "500m", 4, 10, 20, "jpg")
+    bm = np.asarray(bm.resize((W, H), Image.LANCZOS)).astype(np.float32)
+
+    # colour-match Blue Marble to Esri per hemisphere: fit an affine 3x3+offset colour
+    # transform (least squares) on co-registered pixels in the 76-84.5 deg overlap band
+    alat = np.abs(lat)
+    band = (alat > 76) & (alat < 84.5)
+    t = np.clip((alat - FADE_A) / (FADE_B - FADE_A), 0, 1)
+    t = (t * t * (3 - 2 * t)).astype(np.float32)[:, None, None]  # smoothstep
+    out = eq.copy()
+    for hemi in (lat > 0, lat < 0):
+        rows = band & hemi
+        a = eq[rows][:, ::4].reshape(-1, 3)
+        b = bm[rows][:, ::4].reshape(-1, 3)
+        X = np.hstack([b, np.ones((len(b), 1), np.float32)])
+        # ridge-regularised toward identity: near-grey ice makes the plain fit ill-conditioned
+        lam = len(b) * 50.0
+        D = np.diag([1.0, 1.0, 1.0, 0.0])
+        I0 = np.vstack([np.eye(3), np.zeros((1, 3))])
+        X64, a64 = X.astype(np.float64), a.astype(np.float64)
+        M = np.linalg.solve(X64.T @ X64 + lam * D, X64.T @ a64 + lam * D @ I0)
+        print("  colour transform\n", M.round(3))
+        h = bm[hemi]
+        bm[hemi] = (h.reshape(-1, 3) @ M[:3] + M[3]).reshape(h.shape)
+        out[hemi] = eq[hemi] * (1 - t[hemi]) + bm[hemi] * t[hemi]
+
+    img = Image.fromarray(np.clip(out + 0.5, 0, 255).astype(np.uint8))
+    os.makedirs(OUT, exist_ok=True)
+    img.save(os.path.join(OUT, "earth_day.jpg"), quality=92, optimize=True, progressive=True)
+    img.resize((4096, 2048), Image.LANCZOS).save(os.path.join(OUT, "earth_day_4k.jpg"), quality=92, optimize=True, progressive=True)
+    print("done")
+
+
+if __name__ == "__main__":
+    main()

intro-sequence/tools/imagery/build_hero.py

@@ -0,0 +1,133 @@
+"""Deliverable 4: Esri World Imagery 'synthetic screenshots' of iconic places.
+
+For each location: <slug>_wide.jpg (zoom 13) and <slug>_close.jpg (zoom 18,
+falling back to 17/16 when Esri serves "Map data not yet available"
+placeholder tiles), both 1536x1024 centred on the point. Writes index.json.
+
+Usage: python3 build_hero.py [--contact DIR]   (contact sheets for visual QA)
+       Per-location overrides: CLOSE_ZOOM_OVERRIDES below.
+"""
+import io
+import json
+import math
+import os
+import sys
+import numpy as np
+from PIL import Image
+from common import OUT, esri_jobs, fetch_many
+
+HERO = os.path.join(OUT, "hero")
+CW, CH = 1536, 1024
+TS = 256
+
+LOCATIONS = [
+    ("manhattan", "Midtown Manhattan", 40.7580, -73.9855),
+    ("palm_jumeirah", "Palm Jumeirah", 25.1124, 55.1390),
+    ("singapore_port", "Port of Singapore (Pasir Panjang Terminal)", 1.2730, 103.7690),  # was 1.2650,103.8180 (Keppel Bay residential, no port),
+    ("shibuya", "Shibuya Crossing", 35.6595, 139.7005),
+    ("arc_de_triomphe", "Arc de Triomphe", 48.8738, 2.2950),
+    ("giza", "Giza Pyramids", 29.9792, 31.1342),
+    ("rotterdam_port", "Port of Rotterdam", 51.9500, 4.0500),
+    ("lax", "Los Angeles International Airport", 33.9416, -118.4085),
+    ("hong_kong", "Victoria Harbour, Hong Kong", 22.2930, 114.1700),
+    ("panama_canal", "Panama Canal, Miraflores Locks", 8.9966, -79.5915),  # was 9.0800,-79.6800 (blurry jungle/lake shore),
+    ("sydney_opera", "Sydney Opera House", -33.8568, 151.2153),
+    ("kennedy_lc39a", "Kennedy Space Center LC-39A", 28.6083, -80.6041),
+    ("heathrow", "London Heathrow Airport", 51.4700, -0.4543),
+    ("rio_maracana", "Maracana Stadium, Rio de Janeiro", -22.9122, -43.2302),
+    ("venice", "Venice", 45.4340, 12.3388),
+    ("las_vegas_strip", "Las Vegas Strip", 36.1147, -115.1728),
+    ("vatican", "Vatican City", 41.9022, 12.4539),
+    ("burj_khalifa", "Burj Khalifa, Dubai", 25.1972, 55.2744),
+    ("golden_gate", "Golden Gate Bridge", 37.8199, -122.4783),
+    ("kremlin", "Moscow Kremlin", 55.7520, 37.6175),
+    ("tiananmen", "Tiananmen Square, Beijing", 39.9037, 116.3917),  # was 39.9055,116.3976 (east of the square),
+    ("mumbai_port", "Mumbai Port", 18.9400, 72.8400),
+    ("suez_canal", "Suez Canal, Ismailia", 30.6141, 32.3228),  # was 30.5850,32.2650 (Ismailia city blocks, canal off-frame),
+    ("pentagon", "The Pentagon", 38.8719, -77.0563),
+]
+
+WIDE_ZOOM = 13
+CLOSE_ZOOM = 18
+CLOSE_ZOOM_OVERRIDES = {}  # slug -> zoom, set after visual QA if needed
+DROP = set()               # slugs rejected after visual QA
+
+
+def world_px(lat, lon, z):
+    n = TS * 2 ** z
+    x = (lon + 180.0) / 360.0 * n
+    s = math.sin(math.radians(lat))
+    y = (0.5 - math.log((1 + s) / (1 - s)) / (4 * math.pi)) * n
+    return x, y
+
+
+def is_placeholder(tile):
+    a = np.asarray(tile).astype(np.float32)
+    m = a.reshape(-1, 3).mean(0)
+    return a.std() < 8 and abs(m[0] - m[1]) < 4 and abs(m[1] - m[2]) < 4
+
+
+def render(lat, lon, z):
+    """Return (image, placeholder_fraction)."""
+    cx, cy = world_px(lat, lon, z)
+    x0, y0 = int(round(cx - CW / 2)), int(round(cy - CH / 2))
+    tx0, ty0 = x0 // TS, y0 // TS
+    tx1, ty1 = (x0 + CW - 1) // TS, (y0 + CH - 1) // TS
+    n = 2 ** z
+    coords = [(tx % n, ty) for ty in range(ty0, ty1 + 1) for tx in range(tx0, tx1 + 1)]
+    data = fetch_many(esri_jobs(z, coords), desc=f"z{z}")
+    canvas = Image.new("RGB", ((tx1 - tx0 + 1) * TS, (ty1 - ty0 + 1) * TS))
+    ph = 0
+    for ty in range(ty0, ty1 + 1):
+        for tx in range(tx0, tx1 + 1):
+            b = data.get((tx % n, ty))
+            if b is None:
+                ph += 1
+                continue
+            t = Image.open(io.BytesIO(b)).convert("RGB")
+            if is_placeholder(t):
+                ph += 1
+            canvas.paste(t, ((tx - tx0) * TS, (ty - ty0) * TS))
+    crop = canvas.crop((x0 - tx0 * TS, y0 - ty0 * TS, x0 - tx0 * TS + CW, y0 - ty0 * TS + CH))
+    return crop, ph / len(coords)
+
+
+def main():
+    os.makedirs(HERO, exist_ok=True)
+    contact = None
+    if "--contact" in sys.argv:
+        contact = sys.argv[sys.argv.index("--contact") + 1]
+        os.makedirs(contact, exist_ok=True)
+    index = []
+    for slug, name, lat, lon in LOCATIONS:
+        if slug in DROP:
+            for k in ("wide", "close"):
+                p = os.path.join(HERO, f"{slug}_{k}.jpg")
+                if os.path.exists(p):
+                    os.remove(p)
+            print(f"{slug}: dropped")
+            continue
+        wide, _ = render(lat, lon, WIDE_ZOOM)
+        z = CLOSE_ZOOM_OVERRIDES.get(slug, CLOSE_ZOOM)
+        while True:
+            close, ph = render(lat, lon, z)
+            if ph == 0 or z <= 16:
+                break
+            print(f"  {slug}: {ph:.0%} placeholder tiles at z{z}, falling back")
+            z -= 1
+        wide.save(os.path.join(HERO, f"{slug}_wide.jpg"), quality=92, optimize=True)
+        close.save(os.path.join(HERO, f"{slug}_close.jpg"), quality=92, optimize=True)
+        index.append({"slug": slug, "name": name, "lat": lat, "lon": lon, "close_zoom": z})
+        print(f"{slug}: close z{z}")
+        if contact:
+            sheet = Image.new("RGB", (1536, 512))
+            sheet.paste(wide.resize((768, 512), Image.LANCZOS), (0, 0))
+            sheet.paste(close.resize((768, 512), Image.LANCZOS), (768, 0))
+            sheet.save(os.path.join(contact, f"{slug}.jpg"), quality=85)
+    with open(os.path.join(HERO, "index.json"), "w") as f:
+        json.dump(index, f, indent=2)
+    print(f"{len(index)} locations written")
+
+
+if __name__ == "__main__":
+    main()

intro-sequence/tools/imagery/build_night.py

@@ -0,0 +1,20 @@
+"""Deliverable 2: earth_night.jpg (8192x4096) + earth_night_4k.jpg (4096x2048).
+
+NASA Black Marble (layer VIIRS_Black_Marble, 2016 annual composite) from GIBS
+EPSG:4326 level 4 (20x10 tiles of 512px = 10240x5120), Lanczos-downsampled.
+Colour kept as served.
+"""
+import os
+from PIL import Image
+from common import OUT, gibs_mosaic
+
+Image.MAX_IMAGE_PIXELS = None
+LAYER = os.environ.get("NIGHT_LAYER", "VIIRS_Black_Marble")
+TIME = os.environ.get("NIGHT_TIME", "2016-01-01")
+EXT = "png" if LAYER == "VIIRS_Black_Marble" else "jpg"
+
+m = gibs_mosaic(LAYER, TIME if LAYER == "VIIRS_Black_Marble" else None, "500m", 4, 10, 20, EXT)
+big = m.resize((8192, 4096), Image.LANCZOS)
+big.save(os.path.join(OUT, "earth_night.jpg"), quality=92, optimize=True, progressive=True)
+big.resize((4096, 2048), Image.LANCZOS).save(os.path.join(OUT, "earth_night_4k.jpg"), quality=92, optimize=True, progressive=True)
+print("done", LAYER, TIME)

intro-sequence/tools/imagery/build_quadtree_tiles.py

@@ -0,0 +1,15 @@
+"""Deliverable 5: Esri World Imagery z3 (8x8) and z4 (16x16) tiles for the quadtree indexing effect."""
+import os, shutil
+from common import OUT, esri_jobs, fetch_many, esri_tile_path
+
+for z in (3, 4):
+    n = 2 ** z
+    d = os.path.join(OUT, f"tiles_z{z}")
+    os.makedirs(d, exist_ok=True)
+    coords = [(x, y) for y in range(n) for x in range(n)]
+    res = fetch_many(esri_jobs(z, coords), desc=f"esri z{z}")
+    bad = [k for k, v in res.items() if v is None]
+    for x, y in coords:
+        if res[(x, y)] is not None:
+            shutil.copyfile(esri_tile_path(z, x, y), os.path.join(d, f"z{z}_{x}_{y}.jpg"))
+    print(f"z{z}: {len(coords)-len(bad)} tiles written, {len(bad)} failed")

intro-sequence/tools/imagery/common.py

@@ -0,0 +1,116 @@
+"""Shared helpers: polite cached tile fetching for Esri World Imagery and NASA GIBS."""
+import io
+import os
+import sys
+import time
+import threading
+from concurrent.futures import ThreadPoolExecutor, as_completed
+
+import requests
+from PIL import Image
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+CACHE = os.path.join(HERE, "cache")
+ROOT = os.path.abspath(os.path.join(HERE, "..", ".."))
+OUT = os.path.join(ROOT, "imagery")
+
+MAX_WORKERS = 8
+UA = "gods-eye-view-intro/1.0 (texture prep; contact: project maintainer)"
+
+ESRI = "https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}"
+GIBS4326 = "https://gibs.earthdata.nasa.gov/wmts/epsg4326/best/{layer}/default/{time}/{tms}/{z}/{row}/{col}.{ext}"
+
+_local = threading.local()
+
+
+def _session():
+    s = getattr(_local, "s", None)
+    if s is None:
+        s = requests.Session()
+        s.headers["User-Agent"] = UA
+        _local.s = s
+    return s
+
+
+def fetch(url, cache_path, retries=6):
+    """Return raw bytes for url, caching to cache_path. Retries with backoff."""
+    if os.path.exists(cache_path) and os.path.getsize(cache_path) > 0:
+        with open(cache_path, "rb") as f:
+            return f.read()
+    os.makedirs(os.path.dirname(cache_path), exist_ok=True)
+    last = None
+    for attempt in range(retries):
+        try:
+            r = _session().get(url, timeout=60)
+            if r.status_code == 200 and r.content:
+                tmp = cache_path + ".part"
+                with open(tmp, "wb") as f:
+                    f.write(r.content)
+                os.replace(tmp, cache_path)
+                return r.content
+            if r.status_code in (400, 404):
+                last = f"HTTP {r.status_code}"
+                break
+            last = f"HTTP {r.status_code}"
+        except Exception as e:  # network hiccup
+            last = repr(e)
+        time.sleep(min(30, 1.5 * 2 ** attempt))
+    raise RuntimeError(f"failed {url}: {last}")
+
+
+def fetch_many(jobs, desc=""):
+    """jobs: list of (key, url, cache_path). Returns {key: bytes or None}."""
+    out = {}
+    done = 0
+    with ThreadPoolExecutor(MAX_WORKERS) as ex:
+        futs = {ex.submit(fetch, u, p): k for k, u, p in jobs}
+        for f in as_completed(futs):
+            k = futs[f]
+            try:
+                out[k] = f.result()
+            except Exception as e:
+                print(f"  ! {e}", file=sys.stderr)
+                out[k] = None
+            done += 1
+            if done % 100 == 0 or done == len(jobs):
+                print(f"  {desc} {done}/{len(jobs)}", flush=True)
+    return out
+
+
+def esri_tile_path(z, x, y):
+    return os.path.join(CACHE, "esri", str(z), str(y), f"{x}.jpg")
+
+
+def esri_jobs(z, coords):
+    return [((x, y), ESRI.format(z=z, x=x, y=y), esri_tile_path(z, x, y)) for x, y in coords]
+
+
+def gibs_path(layer, time_, tms, z, row, col, ext):
+    return os.path.join(CACHE, "gibs", layer, time_ or "default", tms, str(z), str(row), f"{col}.{ext}")
+
+
+def gibs_jobs(layer, time_, tms, z, rows, cols, ext):
+    t = time_ or "default"
+    return [((r, c), GIBS4326.format(layer=layer, time=t, tms=tms, z=z, row=r, col=c, ext=ext),
+             gibs_path(layer, time_, tms, z, r, c, ext)) for r in range(rows) for c in range(cols)]
+
+
+def decode(b, mode="RGB"):
+    return Image.open(io.BytesIO(b)).convert(mode)
+
+
+def gibs_mosaic(layer, time_, tms, z, rows, cols, ext, mode="RGB"):
+    """Fetch and stitch a full-globe GIBS EPSG:4326 level (512px tiles)."""
+    jobs = gibs_jobs(layer, time_, tms, z, rows, cols, ext)
+    data = fetch_many(jobs, desc=f"{layer} z{z}")
+    W, H = cols * 512, rows * 512
+    canvas = Image.new(mode, (W, H))
+    missing = 0
+    for (r, c), b in data.items():
+        if b is None:
+            missing += 1
+            continue
+        canvas.paste(decode(b, mode), (c * 512, r * 512))
+    if missing:
+        print(f"  {missing} tiles missing for {layer}", file=sys.stderr)
+    return canvas

intro-sequence/tools/live/build_transit.py

@@ -0,0 +1,82 @@
+"""MBTA static GTFS -> city/boston/transit.json (subway, Mattapan, commuter rail, bus).
+usage: python3 build_transit.py <dir with routes.txt shapes.txt trips.txt>"""
+import csv, json, math, os, sys
+from collections import defaultdict
+sys.path.insert(0, os.path.dirname(__file__))
+from common import SCENES, enu
+ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
+G = sys.argv[1]
+H = SCENES['boston'][2]; M = H + 1000
+
+def rdp(pts, eps):
+    if len(pts) < 3: return pts
+    keep = [False] * len(pts); keep[0] = keep[-1] = True
+    stack = [(0, len(pts) - 1)]
+    while stack:
+        a, b = stack.pop()
+        ax, ay = pts[a]; bx, by = pts[b]; dx, dy = bx - ax, by - ay; L = math.hypot(dx, dy)
+        best, bi = -1, -1
+        for i in range(a + 1, b):
+            px, py = pts[i]
+            d = abs(dy * (px - ax) - dx * (py - ay)) / L if L else math.hypot(px - ax, py - ay)
+            if d > best: best, bi = d, i
+        if best > eps:
+            keep[bi] = True; stack += [(a, bi), (bi, b)]
+    return [p for p, k in zip(pts, keep) if k]
+
+def length(p): return sum(math.hypot(p[i+1][0]-p[i][0], p[i+1][1]-p[i][1]) for i in range(len(p)-1))
+
+routes = {}
+for r in csv.DictReader(open(os.path.join(G, 'routes.txt'), encoding='utf-8-sig')):
+    t = int(r['route_type'])
+    if t not in (0, 1, 2, 3): continue
+    if 'Replacement' in r['route_desc'] or r['route_id'].startswith('Shuttle'): continue
+    name = r['route_short_name'] or r['route_long_name']
+    if t == 3 and r['route_short_name'] and r['route_long_name']:
+        name = f"{r['route_short_name']} {r['route_long_name']}"
+    routes[r['route_id']] = {'name': name, 'color': '#' + (r['route_color'] or '888888').upper(), 'type': t}
+
+shape_rd = {}
+for t in csv.DictReader(open(os.path.join(G, 'trips.txt'), encoding='utf-8-sig')):
+    if t['route_id'] in routes and t['shape_id']:
+        shape_rd.setdefault(t['shape_id'], (t['route_id'], t['direction_id']))
+
+shapes = defaultdict(list)
+for s in csv.DictReader(open(os.path.join(G, 'shapes.txt'), encoding='utf-8-sig')):
+    if s['shape_id'] in shape_rd:
+        shapes[s['shape_id']].append((int(s['shape_pt_sequence']), float(s['shape_pt_lat']), float(s['shape_pt_lon'])))
+
+best = {}  # (route, dir) -> (len_in_square, segments)
+for sid, pts in shapes.items():
+    pts.sort()
+    xy = [enu('boston', la, lo) for _, la, lo in pts]
+    if not any(abs(x) <= H and abs(y) <= H for x, y in xy): continue  # must pass within the square
+    segs, cur = [], []
+    for i, (x, y) in enumerate(xy):
+        if abs(x) <= M and abs(y) <= M:
+            if not cur and i > 0: cur.append(xy[i-1])  # carry edge point
+            cur.append((x, y))
+        elif cur:
+            cur.append((x, y)); segs.append(cur); cur = []
+    if cur: segs.append(cur)
+    segs = [rdp(s, 2.0) for s in segs if len(s) > 1]
+    L = sum(length(s) for s in segs)
+    key = shape_rd[sid]
+    if key not in best or L > best[key][0]: best[key] = (L, segs)
+
+out_shapes, seen = [], set()
+for (rid, d), (L, segs) in sorted(best.items()):
+    for s in segs:
+        flat = tuple(round(v, 1) for p in s for v in p)
+        if (rid, flat) in seen: continue
+        seen.add((rid, flat))
+        out_shapes.append([rid] + list(flat))
+used = {s[0] for s in out_shapes}
+out = {'routes': {k: v for k, v in routes.items() if k in used}, 'shapes': out_shapes,
+       'source': 'MBTA GTFS ' + open(os.path.join(G, 'feed_info.txt')).read().splitlines()[1].split(',"')[1].split('"')[0]}
+json.dump(out, open(os.path.join(ROOT, 'city', 'boston', 'transit.json'), 'w'), separators=(',', ':'))
+bytype = defaultdict(int)
+for k in used: bytype[routes[k]['type']] += 1
+print('routes', len(used), dict(bytype), 'shapes', len(out_shapes), 'pts', sum((len(s)-1)//2 for s in out_shapes))
+print('rail routes:', sorted(k for k in used if routes[k]['type'] != 3))
+print('missing requested:', [k for k in ['Red','Orange','Blue','Green-B','Green-C','Green-D','Green-E','Mattapan'] if k not in used])

intro-sequence/tools/live/common.py

@@ -0,0 +1,15 @@
+import math
+SCENES = {
+    'nyc': (40.7400, -73.9900, 3500),
+    'boston': (42.3555, -71.0605, 3200),
+    'lax': (33.9425, -118.4081, 3500),
+    'bragg': (35.1580, -79.0090, 6000),
+}
+def enu(slug, lat, lon):
+    lat0, lon0, _ = SCENES[slug]
+    x = (lon - lon0) * math.cos(math.radians(lat0)) * 111320
+    y = (lat - lat0) * 110540
+    return round(x, 1), round(y, 1)
+def inside(slug, x, y, margin=0.0):
+    h = SCENES[slug][2] + margin
+    return abs(x) <= h and abs(y) <= h

intro-sequence/tools/live/detect.py

@@ -0,0 +1,76 @@
+"""YOLOv8n (ONNX, CPU) over cctv/cam_*.jpg and cctv/nyc/*.jpg -> cctv/detections.json.
+Model auto-downloads to tools/live/models/yolov8n.onnx (git-ignored)."""
+import glob, json, os, sys, time, requests
+import numpy as np, onnxruntime as ort
+from PIL import Image, ImageDraw
+from collections import Counter
+HERE = os.path.dirname(os.path.abspath(__file__)); ROOT = os.path.abspath(os.path.join(HERE, '..', '..'))
+MODEL = os.path.join(HERE, 'models', 'yolov8n.onnx')
+MODEL_URL = 'https://huggingface.co/Kalray/yolov8/resolve/main/yolov8n.onnx'
+KEEP = {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 5: 'bus', 7: 'truck', 9: 'traffic light', 11: 'stop sign'}
+CONF, IOU, S = 0.16, 0.45, 640
+if not os.path.exists(MODEL):
+    os.makedirs(os.path.dirname(MODEL), exist_ok=True)
+    open(MODEL, 'wb').write(requests.get(MODEL_URL, timeout=120).content)
+sess = ort.InferenceSession(MODEL, providers=['CPUExecutionProvider'])
+inp = sess.get_inputs()[0].name
+
+def nms(b, s, thr):
+    order = s.argsort()[::-1]; keep = []
+    while order.size:
+        i = order[0]; keep.append(i)
+        xx0 = np.maximum(b[i, 0], b[order[1:], 0]); yy0 = np.maximum(b[i, 1], b[order[1:], 1])
+        xx1 = np.minimum(b[i, 2], b[order[1:], 2]); yy1 = np.minimum(b[i, 3], b[order[1:], 3])
+        inter = np.clip(xx1 - xx0, 0, None) * np.clip(yy1 - yy0, 0, None)
+        a = (b[:, 2] - b[:, 0]) * (b[:, 3] - b[:, 1])
+        iou = inter / (a[i] + a[order[1:]] - inter + 1e-9)
+        order = order[1:][iou <= thr]
+    return keep
+
+def detect(path):
+    im = Image.open(path).convert('RGB'); W, H = im.size
+    r = min(S / W, S / H); nw, nh = round(W * r), round(H * r); px, py = (S - nw) // 2, (S - nh) // 2
+    canvas = Image.new('RGB', (S, S), (114, 114, 114)); canvas.paste(im.resize((nw, nh), Image.BILINEAR), (px, py))
+    x = np.asarray(canvas, dtype=np.float32).transpose(2, 0, 1)[None] / 255.0
+    p = sess.run(None, {inp: x})[0][0].T  # 8400 x 84
+    sc = p[:, 4:]; cls = sc.argmax(1); conf = sc.max(1)
+    m = (conf >= CONF) & np.isin(cls, list(KEEP))
+    p, cls, conf = p[m], cls[m], conf[m]
+    if not len(p): return []
+    b = np.stack([p[:, 0] - p[:, 2] / 2, p[:, 1] - p[:, 3] / 2, p[:, 0] + p[:, 2] / 2, p[:, 1] + p[:, 3] / 2], 1)
+    out = []
+    for c in np.unique(cls):  # class-wise NMS
+        idx = np.where(cls == c)[0]
+        for k in nms(b[idx], conf[idx], IOU):
+            j = idx[k]; x0, y0, x1, y1 = b[j]
+            x0 = min(max((x0 - px) / r / W, 0), 1); x1 = min(max((x1 - px) / r / W, 0), 1)
+            y0 = min(max((y0 - py) / r / H, 0), 1); y1 = min(max((y1 - py) / r / H, 0), 1)
+            if x1 - x0 > 0 and y1 - y0 > 0:
+                out.append([round(float(x0), 4), round(float(y0), 4), round(float(x1), 4), round(float(y1), 4), round(float(conf[j]), 3), KEEP[int(c)]])
+    return sorted(out, key=lambda d: -d[4])
+
+COL = {'person': (255, 60, 60), 'car': (60, 200, 255), 'truck': (255, 180, 0), 'bus': (255, 0, 255), 'bicycle': (0, 255, 120),
+       'motorcycle': (180, 255, 0), 'traffic light': (255, 255, 255), 'stop sign': (255, 0, 0)}
+def render(path, dets, dst):
+    im = Image.open(path).convert('RGB'); W, H = im.size; d = ImageDraw.Draw(im)
+    for x0, y0, x1, y1, c, n in dets:
+        d.rectangle([x0 * W, y0 * H, x1 * W, y1 * H], outline=COL[n], width=2)
+        d.text((x0 * W + 2, max(0, y0 * H - 11)), f'{n} {c:.2f}', fill=COL[n])
+    im.save(dst, quality=90)
+
+if __name__ == '__main__':
+    files = sorted(glob.glob(os.path.join(ROOT, 'cctv', 'cam_*.jpg'))) + sorted(glob.glob(os.path.join(ROOT, 'cctv', 'nyc', '*.jpg')))
+    res, tot, t0 = {}, Counter(), time.time()
+    for f in files:
+        rel = os.path.relpath(f, os.path.join(ROOT, 'cctv'))
+        res[rel] = detect(f); tot.update(d[5] for d in res[rel])
+    dt = time.time() - t0
+    json.dump(res, open(os.path.join(ROOT, 'cctv', 'detections.json'), 'w'), separators=(',', ':'))
+    print('images', len(files), 'secs', round(dt, 1), 'ms/img', round(1000 * dt / max(1, len(files))))
+    print('totals', dict(tot.most_common()), 'all', sum(tot.values()))
+    print('nyc totals', dict(Counter(d[5] for k, v in res.items() if k.startswith('nyc/') for d in v)))
+    picks = sys.argv[1:] or [max((k for k in res if k.startswith('nyc/')), key=lambda k: len(res[k])),
+                             max((k for k in res if not k.startswith('nyc/')), key=lambda k: len(res[k])),
+                             max(res, key=lambda k: sum(d[5] == 'person' for d in res[k]))]
+    for i, k in enumerate(picks, 1):
+        render(os.path.join(ROOT, 'cctv', k), res[k], os.path.join(HERE, f'det_check_{i}.jpg')); print('render', i, k, len(res[k]))

intro-sequence/tools/live/fetch_adsb.py

@@ -0,0 +1,72 @@
+"""Poll live ADS-B (adsb.lol, fallback adsb.fi) around each scene 3x, 20 s apart.
+Writes city/<slug>/air.json with latest sample per aircraft + short track history."""
+import json, os, sys, time, requests
+sys.path.insert(0, os.path.dirname(__file__))
+from common import SCENES, enu
+ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
+RAD = {'nyc': 25, 'lax': 25, 'bragg': 25, 'boston': 20}
+HELI_TYPES = {'EC35','EC30','EC45','EC55','EC20','EC25','EC75','EC13','EC40','AS50','AS55','AS65','AS32','AS3B','H125','H130','H135','H145','H160','H175','B06','B06T','B407','B412','B427','B429','B430','B47G','B505','B212','B222','B230','B105','BK17','R22','R44','R66','S76','S92','S61','S64','S70','H60','UH60','MH60','HH60','H47','CH47','H53','A109','A119','A139','A169','A189','AW09','MI8','MI17','UH1','UH1Y','AH1','AH64','H64','V22','MV22','CABR','G2CA','EN28','EN48','H269','H500','MD52','MD60','NH90','LYNX','PUMA','GAZL','EH10','H1','B505'}
+H = {'User-Agent': 'gods-eye-view-intro/1.0 (film research)'}
+def fetch(slug):
+    lat, lon, _ = SCENES[slug]; nm = RAD[slug]
+    for url, key in ((f'https://api.adsb.lol/v2/point/{lat}/{lon}/{nm}', 'ac'),
+                     (f'https://opendata.adsb.fi/api/v2/lat/{lat}/lon/{lon}/dist/{nm}', 'aircraft')):
+        try:
+            r = requests.get(url, headers=H, timeout=20); r.raise_for_status(); j = r.json()
+            ac = j.get('ac') or j.get('aircraft') or []
+            now = j.get('now') or time.time() * 1000
+            return url, now / 1000 if now > 1e11 else now, ac
+        except Exception as e:
+            print(slug, 'fail', url, e, file=sys.stderr)
+    return None, time.time(), []
+def num(v):
+    try: return float(v)
+    except Exception: return None
+def conv(slug, a):
+    lat, lon = num(a.get('lat')), num(a.get('lon'))
+    if lat is None or lon is None:
+        lp = a.get('lastPosition') or {}
+        lat, lon = num(lp.get('lat')), num(lp.get('lon'))
+    if lat is None: return None
+    x, y = enu(slug, lat, lon)
+    ab = a.get('alt_baro')
+    if ab == 'ground': alt = 0.0
+    else:
+        v = num(ab)
+        if v is None: v = num(a.get('alt_geom'))
+        alt = round(v * 0.3048, 1) if v is not None else None
+    trk = num(a.get('track')); trk = num(a.get('true_heading')) if trk is None else trk
+    gs = num(a.get('gs')); gs = round(gs * 0.514444, 1) if gs is not None else None
+    vr = num(a.get('baro_rate')); vr = num(a.get('geom_rate')) if vr is None else vr
+    vr = round(vr * 0.00508, 2) if vr is not None else None
+    return [x, y, alt, trk, gs, vr, (a.get('flight') or '').strip(), a.get('t') or '', a.get('category') or '']
+def main():
+    polls = {s: [] for s in SCENES}
+    for i in range(3):
+        t0 = time.time()
+        for s in SCENES:
+            url, t, ac = fetch(s); polls[s].append((url, t, ac)); print(i, s, len(ac), url, flush=True)
+        if i < 2: time.sleep(max(0, 20 - (time.time() - t0)))
+    summary = {}
+    for s in SCENES:
+        latest, tracks, src = {}, {}, set()
+        tlast = 0
+        for url, t, ac in polls[s]:
+            if url: src.add(url.split('/')[2])
+            tlast = max(tlast, t)
+            for a in ac:
+                hx = a.get('hex'); row = conv(s, a)
+                if not hx or row is None: continue
+                if (num(a.get('seen_pos')) or 0) > 60: continue
+                latest[hx] = row
+                tr = tracks.setdefault(hx, [])
+                p = [row[0], row[1], row[2]]
+                if not tr or tr[-1][:2] != p[:2]: tr.append(p)
+        heli = [h for h, r in latest.items() if r[8] == 'A7' or r[7] in HELI_TYPES]
+        out = {'t': int(tlast), 'source': sorted(src), 'radius_nm': RAD[s], 'hex': list(latest.keys()),
+               'a': list(latest.values()), 'tracks': {h: v for h, v in tracks.items() if len(v) > 1}}
+        json.dump(out, open(os.path.join(ROOT, 'city', s, 'air.json'), 'w'), separators=(',', ':'))
+        summary[s] = {'aircraft': len(latest), 'with_track': len(out['tracks']), 'heli': len(heli),
+                      'heli_list': [[latest[h][6], latest[h][7], latest[h][8], latest[h][2]] for h in heli]}
+    print(json.dumps(summary, indent=1))
+if __name__ == '__main__': main()

intro-sequence/tools/live/fetch_mbta_vehicles.py

@@ -0,0 +1,21 @@
+"""Live MBTA vehicle positions -> city/boston/vehicles.json (square + 1 km)."""
+import json, os, sys, requests
+from collections import Counter
+sys.path.insert(0, os.path.dirname(__file__))
+from common import enu, inside
+ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
+j = requests.get('https://cdn.mbta.com/realtime/VehiclePositions_enhanced.json', timeout=30).json()
+rows, total = [], 0
+for e in j['entity']:
+    v = e.get('vehicle') or {}; p = v.get('position') or {}
+    if 'latitude' not in p: continue
+    total += 1
+    x, y = enu('boston', p['latitude'], p['longitude'])
+    if not inside('boston', x, y, 1000): continue
+    rid = (v.get('trip') or {}).get('route_id', '')
+    lab = (v.get('vehicle') or {}).get('label') or (v.get('vehicle') or {}).get('id', '')
+    sp = p.get('speed'); rows.append([x, y, p.get('bearing'), round(sp, 2) if sp is not None else None, rid, lab])
+out = {'t': int(j['header']['timestamp']), 'source': 'cdn.mbta.com VehiclePositions_enhanced.json', 'v': rows}
+json.dump(out, open(os.path.join(ROOT, 'city', 'boston', 'vehicles.json'), 'w'), separators=(',', ':'))
+c = Counter(r[4].split('-')[0] if r[4].startswith(('Green', 'CR')) else ('bus' if r[4][:1].isdigit() or r[4][:2] in ('SL','CT') else r[4]) for r in rows)
+print('t', out['t'], 'feed total', total, 'in square+1km', len(rows), dict(c))

intro-sequence/tools/live/fetch_nyc_cams.py

@@ -0,0 +1,53 @@
+"""NYC DOT TMC cameras -> city/nyc/cameras.json + current stills for ~24 nearest cams."""
+import hashlib, io, json, os, sys, time, requests
+import numpy as np
+from PIL import Image, ImageOps
+from collections import Counter
+sys.path.insert(0, os.path.dirname(__file__))
+from common import enu, inside
+ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
+OUT = os.path.join(ROOT, 'cctv', 'nyc'); DBG = os.path.join(os.path.dirname(__file__), 'nyc_rejects')
+os.makedirs(OUT, exist_ok=True); os.makedirs(DBG, exist_ok=True)
+H = {'User-Agent': 'gods-eye-view-intro/1.0'}
+cat = requests.get('https://webcams.nyctmc.org/api/cameras', headers=H, timeout=30).json()
+cams = []
+for c in cat:
+    if str(c.get('isOnline')).lower() != 'true': continue
+    try: lat, lon = float(c['latitude']), float(c['longitude'])
+    except Exception: continue
+    x, y = enu('nyc', lat, lon)
+    if inside('nyc', x, y): cams.append((x, y, c['id'], c['name'].strip(), lat, lon))
+json.dump([[x, y, i, n] for x, y, i, n, _, _ in cams], open(os.path.join(ROOT, 'city', 'nyc', 'cameras.json'), 'w'), separators=(',', ':'))
+print('catalog', len(cat), 'online in square', len(cams))
+cams.sort(key=lambda c: c[0]**2 + c[1]**2)
+for f in os.listdir(OUT):
+    if f.startswith('cam_') and f.endswith('.jpg'): os.remove(os.path.join(OUT, f))
+idx, rejects, hashes, raw_imgs = [], Counter(), Counter(), []
+fetched_utc = time.strftime('%Y-%m-%dT%H:%M:%SZ', time.gmtime())
+for x, y, cid, name, lat, lon in cams[:80]:
+    if len(raw_imgs) >= 40: break
+    try:
+        r = requests.get(f'https://webcams.nyctmc.org/api/cameras/{cid}/image', headers=H, timeout=20)
+        r.raise_for_status(); im = Image.open(io.BytesIO(r.content)).convert('RGB')
+    except Exception as e:
+        rejects['error'] += 1; continue
+    h = hashlib.md5(r.content).hexdigest(); hashes[h] += 1
+    g = np.asarray(im.convert('L'), dtype=np.float32)
+    raw_imgs.append(dict(x=x, y=y, id=cid, name=name, lat=lat, lon=lon, im=im, h=h, mean=float(g.mean()), std=float(g.std()), size=im.size, n=len(r.content)))
+n = 0
+for d in raw_imgs:
+    reason = None
+    if hashes[d['h']] > 1: reason = 'duplicate/placeholder'
+    elif d['mean'] < 14: reason = 'black'
+    elif d['std'] < 10: reason = 'flat'
+    elif d['size'][0] < 200: reason = 'tiny'
+    if reason:
+        rejects[reason] += 1; d['im'].save(os.path.join(DBG, f"{reason.split('/')[0]}_{d['id'][:8]}.jpg")); continue
+    if n >= 24: break
+    n += 1; fn = f'cam_{n:03d}.jpg'
+    ImageOps.fit(d['im'], (640, 360), Image.LANCZOS).save(os.path.join(OUT, fn), quality=88)
+    idx.append({'file': fn, 'id': d['id'], 'name': d['name'], 'x': d['x'], 'y': d['y'], 'lat': d['lat'], 'lon': d['lon'],
+                'orig_size': list(d['size']), 'fetched_utc': fetched_utc, 'source': 'NYC DOT TMC webcams.nyctmc.org'})
+    print(fn, d['name'], d['size'], round(d['mean']), round(d['std']), round((d['x']**2+d['y']**2)**.5))
+json.dump(idx, open(os.path.join(OUT, 'index.json'), 'w'), indent=1)
+print('saved', n, 'rejects', dict(rejects), 'tried', len(raw_imgs))

intro-sequence/tools/render-all.sh

@@ -0,0 +1,15 @@
+#!/usr/bin/env bash
+# Render one format in 8 s chunks (skips chunks already on disk), then concat.
+#   tools/render-all.sh 1920 1080 16x9
+set -u
+W=$1; H=$2; TAG=$3
+CH=240; TOTAL=${4:-2850}
+mkdir -p out/${PREFIX:-}chunks_$TAG
+for ((s=0; s<TOTAL; s+=CH)); do
+  e=$((s+CH)); f=out/${PREFIX:-}chunks_$TAG/c_$(printf %05d $s).mp4
+  [ -s "$f" ] && continue
+  e=$(( e > TOTAL ? TOTAL : e ))
+  node tools/render.mjs --port ${PORT:-8766} --w $W --h $H --from $s --to $e --video "$f.tmp.mp4" --crf 14 --preset slow && mv "$f.tmp.mp4" "$f"
+done
+ls out/${PREFIX:-}chunks_$TAG/c_*.mp4 | sed "s|^|file '$PWD/|; s|$|'|" > out/${PREFIX:-}chunks_$TAG/list.txt
+ffmpeg -y -loglevel error -f concat -safe 0 -i out/${PREFIX:-}chunks_$TAG/list.txt -c copy out/${PREFIX:-}video_$TAG.mp4 && echo "CONCAT OK $TAG"

intro-sequence/tools/render.mjs

@@ -0,0 +1,91 @@
+// Deterministic frame renderer: drives src/main.js frame by frame in headless
+// Chromium and either writes stills or pipes straight into ffmpeg.
+//
+//   node tools/render.mjs --w 1920 --h 1080 --frames 480,900,1500 --out out/stills
+//   node tools/render.mjs --w 1920 --h 1080 --from 0 --to 2160 --video out/video_16x9.mp4
+import { chromium } from 'playwright-core';
+import { spawn } from 'node:child_process';
+import fs from 'node:fs';
+import path from 'node:path';
+
+const args = Object.fromEntries(
+  process.argv
+    .slice(2)
+    .join(' ')
+    .split('--')
+    .filter(Boolean)
+    .map((s) => {
+      const [k, ...v] = s.trim().split(' ');
+      return [k, v.join(' ') || true];
+    }),
+);
+const W = +args.w || 1920;
+const H = +args.h || 1080;
+const URL = `http://127.0.0.1:${args.port || 8765}/index.html?w=${W}&h=${H}`;
+const CHROME = '/opt/pw-browsers/chromium-1194/chrome-linux/chrome';
+
+const browser = await chromium.launch({
+  executablePath: CHROME,
+  args: ['--use-gl=angle', '--use-angle=swiftshader', '--enable-unsafe-swiftshader', '--ignore-gpu-blocklist', '--disable-gpu-vsync', '--js-flags=--max-old-space-size=8192'],
+});
+const page = await browser.newPage({ viewport: { width: W, height: H }, deviceScaleFactor: 1 });
+page.on('console', (m) => {
+  const t = m.text();
+  if (/error|warn|missing|\[gev\]/i.test(t)) console.log('  page:', t.slice(0, 300));
+});
+page.on('pageerror', (e) => console.log('  PAGE ERROR:', e.message));
+await page.goto(URL);
+await page.waitForFunction(() => window.__status === 'ready' || String(window.__status).startsWith('error'), null, { timeout: 600000, polling: 500 });
+const st = await page.evaluate(() => window.__status);
+if (st !== 'ready') {
+  console.error('init failed:', st);
+  process.exit(1);
+}
+const info = await page.evaluate(() => ({ counts: GEV.counts, heroes: GEV.heroes, cams: GEV.cams, frames: GEV.frames }));
+console.log('ready', JSON.stringify(info));
+
+const cdp = await page.context().newCDPSession(page);
+async function grab(format = 'png') {
+  const r = await cdp.send('Page.captureScreenshot', { format, quality: format === 'jpeg' ? 96 : undefined, fromSurface: true, captureBeyondViewport: false });
+  return Buffer.from(r.data, 'base64');
+}
+
+let frames = [];
+if (args.frames) frames = String(args.frames).split(',').map((x) => (x.includes('s') ? Math.round(parseFloat(x) * 30) : +x));
+else {
+  const from = +(args.from || 0);
+  const to = +(args.to || info.frames);
+  const step = +(args.step || 1);
+  for (let f = from; f < to; f += step) frames.push(f);
+}
+
+let ff = null;
+if (args.video) {
+  fs.mkdirSync(path.dirname(args.video), { recursive: true });
+  ff = spawn('ffmpeg', ['-y', '-loglevel', 'error', '-f', 'image2pipe', '-framerate', '30', '-c:v', 'png', '-i', '-', '-c:v', 'libx264', '-preset', args.preset || 'slow', '-crf', String(args.crf || 14), '-pix_fmt', 'yuv420p', '-colorspace', 'bt709', '-color_primaries', 'bt709', '-color_trc', 'bt709', '-movflags', '+faststart', args.video], { stdio: ['pipe', 'inherit', 'inherit'] });
+} else {
+  fs.mkdirSync(args.out || 'out/stills', { recursive: true });
+}
+
+const t0 = Date.now();
+for (let i = 0; i < frames.length; i++) {
+  const f = frames[i];
+  await page.evaluate((fr) => window.GEV.renderFrame(fr), f);
+  const buf = await grab('png');
+  if (ff) {
+    if (!ff.stdin.write(buf)) await new Promise((r) => ff.stdin.once('drain', r));
+  } else {
+    fs.writeFileSync(path.join(args.out || 'out/stills', `${args.prefix || 'f'}_${String(f).padStart(5, '0')}.png`), buf);
+  }
+  if (i % 30 === 0 || i === frames.length - 1) {
+    const el = (Date.now() - t0) / 1000;
+    const per = el / (i + 1);
+    console.log(`frame ${f} (${i + 1}/${frames.length}) ${per.toFixed(2)} s/frame, eta ${((frames.length - i - 1) * per / 60).toFixed(1)} min`);
+  }
+}
+if (ff) {
+  ff.stdin.end();
+  await new Promise((r) => ff.on('close', r));
+}
+await browser.close();
+console.log('done in', ((Date.now() - t0) / 60000).toFixed(1), 'min');

intro-sequence/tools/sheet.py

@@ -0,0 +1,19 @@
+# usage: python3 tools/sheet.py <dir> <out_prefix> [per_sheet] [cell_w]
+import sys, glob
+from PIL import Image
+d, outp = sys.argv[1], sys.argv[2]
+per = int(sys.argv[3]) if len(sys.argv) > 3 else 4
+cw = int(sys.argv[4]) if len(sys.argv) > 4 else 960
+fs = sorted(glob.glob(d + '/*.png'))
+for s in range(0, len(fs), per):
+    group = fs[s:s + per]
+    ims = [Image.open(f) for f in group]
+    w0, h0 = ims[0].size
+    ch = int(cw * h0 / w0)
+    cols = 2 if w0 > h0 else 4
+    rows = (len(ims) + cols - 1) // cols
+    sheet = Image.new('RGB', (cw * cols, ch * rows))
+    for i, im in enumerate(ims):
+        sheet.paste(im.resize((cw, ch), Image.LANCZOS), ((i % cols) * cw, (i // cols) * ch))
+    sheet.save(f'{outp}_{s // per:02d}.jpg', quality=88)
+    print(f'{outp}_{s // per:02d}.jpg', [f.split('/')[-1] for f in group])

package.json

@@ -277,7 +277,6 @@
     "./tools/mcp": "./src/tools/mcp/index.js",
     "./tools/panel": "./src/tools/panel.js",
     "./tools/services": "./src/tools/services.js",
-    "./view": "./src/view/index.js",
+    "./view": "./src/view/index.js"
-    "./agent/world-packet": "./src/agent/worldPacket.js"
   }
 }

scripts/format-scope.json

@@ -96,7 +96,6 @@
   "server/providers/space/launch-library.js",
   "src/data/spaceProviderRequests.js",
   "src/tooling/spaceProviders.test.mjs",
-  "src/tooling/ll2Integration.test.mjs",
   "server/providers/terrain.js",
   "server/providers/traffic.js",
   "server/providers/firms.js",
@@ -447,7 +446,6 @@
   "src/data/rocketLaunches.js",
   "src/layers/satellites/source.test.mjs",
   "src/layers/launches/source.test.mjs",
-  "src/layers/launches/ingestion.test.mjs",
   "src/layers/installations/lifecycle.js",
   "src/layers/installations/viewport.js",
   "src/layers/installations/controls.js",
@@ -557,8 +555,6 @@
   "src/data/cctvNswSource.test.mjs",
   "src/data/cctvTxdotSource.test.mjs",
   "src/layers/cctv/source.test.mjs",
-  "src/layers/cctv/frames.test.mjs",
-  "src/layers/cctv/rendering.test.mjs",
   "src/data/alprCameras.js",
   "src/data/alprCameras.test.mjs",
   "src/data/dataCredits.test.mjs",
@@ -639,7 +635,6 @@
   "src/voice/control.js",
   "src/voice/realtimeBackend.js",
   "src/voice/realtimeBackend.test.mjs",
-  "src/agent/worldPacket.test.mjs",
   "src/voice/layerSummary.js",
   "build/application-html.js",
   "src/app/sourceSlot.js",
@@ -695,7 +690,6 @@
   "src/ui/shareRestoration.js",
   "src/ui/visualSettings.js",
   "src/ui/panelChrome.js",
-  "src/ui/panelChrome.radioOwnership.test.mjs",
   "src/testSupport/readShellSource.mjs",
   "src/ui/stateOwners.test.mjs",
   "src/layers/flights/records.js",
@@ -1032,7 +1026,6 @@
   "scripts/qa-context-arrivals.mjs",
   "src/tools/catalog.test.mjs",
   "src/tools/area.test.mjs",
-  "src/tools/results.test.mjs",
   "src/tools/queries/queries.test.mjs",
   "src/tools/mcp/mcp.test.mjs",
   "src/tools/localServer.test.mjs",
@@ -1069,6 +1062,5 @@
   "src/ui/flyToDataSource.test.mjs",
   "scripts/assemble-changelog.mjs",
   "src/tooling/changelogFragments.test.mjs",
-  "src/data/gbfsProxyRateLimit.test.mjs",
+  "src/data/gbfsProxyRateLimit.test.mjs"
-  "src/terrainHeightsBounds.test.mjs"
 ]

scripts/package-boundaries.json

@@ -114,11 +114,7 @@
     "exports": ["./server/providers/terrain"],
     "modules": [
       "server/providers/terrain.js",
-      "src/data/terrainHeightsProxy.js",
+      "src/data/terrainHeightsProxy.js"
-      "server/providers/common/rate-limit.js",
-      "src/sources/rateLimit.js",
-      "server/providers/common/same-site.js",
-      "src/localRequestGate.mjs"
     ],
     "external": []
   },
@@ -1044,7 +1040,6 @@
       "src/layers/vessels/tracking.js",
       "src/data/iconOrientation.js",
       "src/data/vesselLabels.js",
-      "src/data/vesselTypes.js",
       "src/layers/vessels/records.js",
       "src/layers/vessels/recordPolicy.js",
       "src/layers/vessels/snapshotRenderer.js",
@@ -1633,15 +1628,7 @@
       "src/i18n/locale.js",
       "src/i18n/locales/es.json",
       "src/i18n/locales/ru.json",
-      "src/ui/statusText.js",
+      "src/ui/statusText.js"
-      "src/voice/providerCommands.js",
-      "src/voice/providerCapabilities.js",
-      "src/voice/geminiSession.js",
-      "src/voice/geminiAudio.js",
-      "src/voice/geminiCaptureWorklet.js",
-      "src/sources/httpBody.js",
-      "src/sources/requestDeadline.js",
-      "src/i18n/marker.js"
     ],
     "external": []
   },
@@ -1854,7 +1841,6 @@
       "src/data/trafficQueue.js",
       "src/data/trailRenderer.js",
       "src/data/vesselLabels.js",
-      "src/data/vesselTypes.js",
       "src/firstRunExperience.js",
       "src/hud.js",
       "src/hudLocality.js",
@@ -2229,7 +2215,6 @@
       "src/voice/commands.js",
       "src/voice/control.js",
       "src/voice/gevActions.js",
-      "src/agent/worldPacket.js",
       "src/voice/speech.js",
       "src/ui/layerNames.js",
       "src/voice/earcon.js",
@@ -2505,12 +2490,7 @@
       "src/layers/airQuality/index.js",
       "src/layers/airQuality/model.js",
       "src/layers/airQuality/source.js",
-      "src/ui/statusText.js",
+      "src/ui/statusText.js"
-      "src/voice/providerCommands.js",
-      "src/voice/providerCapabilities.js",
-      "src/voice/geminiSession.js",
-      "src/voice/geminiAudio.js",
-      "src/voice/geminiCaptureWorklet.js"
     ],
     "external": [
       "hls.js",
@@ -2649,7 +2629,6 @@
       "src/data/trafficQueue.js",
       "src/data/trailRenderer.js",
       "src/data/vesselLabels.js",
-      "src/data/vesselTypes.js",
       "src/keylessGeocoder.js",
       "src/layers/aircraft/classification.js",
       "src/layers/alpr/index.js",
@@ -3398,8 +3377,7 @@
       "src/i18n/locale.js",
       "src/i18n/locales/es.json",
       "src/i18n/locales/ru.json",
-      "src/ui/statusText.js",
+      "src/ui/statusText.js"
-      "src/voice/providerCapabilities.js"
     ],
     "external": []
   },
@@ -3804,7 +3782,6 @@
       "src/tools/queries/maritime.js",
       "src/tools/queries/share.js",
       "src/data/idSwitches.js",
-      "src/data/vesselTypes.js",
       "src/data/layerState.js",
       "src/data/layerStateTokenReservations.json",
       "src/sources/gbfsStations.js",
@@ -3966,18 +3943,5 @@
       "src/i18n/marker.js"
     ],
     "external": []
-  },
-  "agent-world-packet": {
-    "exports": ["./agent/world-packet"],
-    "modules": [
-      "src/agent/worldPacket.js",
-      "src/data/layerSnapshot.js",
-      "src/data/feedState.js",
-      "src/contextModePolicy.js",
-      "src/loadingFeedback.js",
-      "src/data/installationFeedback.js",
-      "src/i18n/marker.js"
-    ],
-    "external": ["cesium"]
   }
 }

scripts/precompute-cctv-heights.mjs

@@ -326,10 +326,8 @@ async function main() {
       'src/data/local_data/cctv_ground_heights/cctv_ground_heights.json',
   );
   let sidecar = await loadSidecar(output);
-  // A cold catalog waits for its slowest pack (Tarktee gets 30 s), so allow
-  // more than that.
   const response = await fetch(`${base}/api/cctv/sources`, {
-    signal: AbortSignal.timeout(60_000),
+    signal: AbortSignal.timeout(30_000),
   });
   if (!response.ok) throw new Error(`Catalog HTTP ${response.status}`);
   const catalog = await response.json();

scripts/qa-cctv-v2.mjs

@@ -11,10 +11,8 @@
  *      exactly once per camera ACTIVATION (the §9.1 obstruction probe) and
  *      never again in steady state; shared mesh-floor sampling fires at most
  *      once per coarse cell during the staggered geometry-load drain, and
- *      actually COMPLETES once tiles load in photoreal mode (>=1 real sample
+ *      actually COMPLETES once tiles load (>=1 real sample — the
- *      — the ceiling alone would pass trivially at Δ=0 if the snap never
+ *      ceiling alone would pass trivially at Δ=0 if the snap never finished),
- *      finished). Globe mode instead proves the rendered mount uses a real
- *      terrain height with zero mesh samples. Sampling
  *      stays flat while idle, and stays flat for non-positional pose edits.
  *   2. Geometry contract: the 5-polyline frustum wireframe + far-cap plane
  *      exist for the active camera, the plane's corners coincide with the
@@ -141,56 +139,6 @@ function record(name, ok, detail) {
 
 const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
 
-// Each page.evaluate is bounded by puppeteer's `protocolTimeout` (default
-// 180s). Waits never come close: they poll from Node (below). The headroom is
-// for the few long evaluates, such as enabling the full ~3,700-camera catalog
-// on a real GPU, and matches the other qa-*.mjs harnesses.
-const PROTOCOL_TIMEOUT_MS = 300_000;
-
-/**
- * Polls an in-page predicate from Node, one short page.evaluate per tick,
- * until it holds or the budget runs out. Used instead of page.waitForFunction
- * for two reasons: its default rAF polling stops in a minimised or hidden
- * headful window (timers keep running, rAF does not), and its result is one
- * CDP call that protocolTimeout cuts off, while the headful drain budget
- * reaches ~50 minutes. A predicate that throws fails the run instead of
- * silently spending the budget.
- * @param {import('puppeteer').Page} page
- * @param {Function} predicate - In-page predicate.
- * @param {object} opts
- * @param {number} opts.timeoutMs - Overall budget.
- * @param {number} [opts.intervalMs=250] - Delay between checks.
- * @param {unknown[]} [opts.args=[]] - Arguments passed to the predicate.
- *   The predicate must return a boolean: its result crosses CDP by value.
- * @returns {Promise<boolean>} True if the predicate held within the budget.
- */
-async function waitForPredicate(
-  page,
-  predicate,
-  { timeoutMs, intervalMs = 250, args = [] },
-) {
-  // performance.now() is monotonic and doesn't advance while the machine
-  // sleeps, so neither a clock change nor a laptop sleep eats the budget.
-  const deadline = performance.now() + timeoutMs;
-  for (;;) {
-    try {
-      if (await page.evaluate(predicate, ...args)) return true;
-    } catch (err) {
-      // A navigation or Vite reload replaces the execution context: poll again.
-      if (
-        !/Execution context was destroyed|Cannot find context/.test(
-          err?.message ?? '',
-        )
-      ) {
-        throw err;
-      }
-    }
-    const remaining = deadline - performance.now();
-    if (remaining <= 0) return false;
-    await sleep(Math.min(intervalMs, remaining));
-  }
-}
-
 // SwiftShader can spend tens of seconds servicing the hover drillPick emitted
 // by page.mouse.move(), before the LEFT_DOWN under test even runs. Position the
 // pointer while ADJUST is disabled, then re-enable it and explicitly render a
@@ -207,58 +155,29 @@ async function positionPointerForGizmoDrag(page, point, frameCount = 3) {
     gev.dataManager.layers
       .get('cctv')
       .module.setParams({ calibrationMode: true });
-    return (await window.__qaRenderFrames(count, 5000)) >= count;
+    const scene = gev.viewer.scene;
-  }, frameCount);
+    let rendered = 0;
-}
+    return new Promise((resolve) => {
-
+      let settled = false;
-/**
+      const finish = (complete) => {
- * Saves a screenshot for human review. These are never a gate, so a capture
+        if (settled) return;
- * that fails (for example when the renderer stalls in a hidden headful window)
+        settled = true;
- * is logged instead of ending the run.
+        clearTimeout(timer);
- * @param {import('puppeteer').Page} page
+        remove();
- * @param {string} file
+        resolve(complete);
- * @param {string} label
+      };
- */
+      const remove = scene.postRender.addEventListener(() => {
-async function saveReviewShot(page, file, label) {
+        rendered += 1;
-  try {
+        if (rendered >= count) {
-    await page.screenshot({ path: file });
+          finish(true);
-    console.log(`  screenshot (${label}) → ${path.relative(REPO_ROOT, file)}`);
+          return;
-  } catch (err) {
+        }
-    console.warn(
-      `  screenshot skipped (${label}): ${path.relative(REPO_ROOT, file)}: ${err?.message ?? err}`,
-    );
-  }
-}
-
-/**
- * Installs window.__qaRenderFrames(count, capMs) in the page: requests renders
- * until `count` frames have passed scene.postRender or capMs runs out, and
- * resolves with the number of frames rendered. The cap keeps a stalled
- * renderer (headful window asleep or hidden) from hanging the CDP call.
- * @param {import('puppeteer').Page} page
- */
-function installRenderFramesHelper(page) {
-  return page.evaluate(() => {
-    window.__qaRenderFrames = (count, capMs) =>
-      new Promise((resolve) => {
-        const scene = window.__godsEyeView.viewer.scene;
-        let frames = 0;
-        const finish = () => {
-          clearTimeout(timer);
-          remove();
-          resolve(frames);
-        };
-        const remove = scene.postRender.addEventListener(() => {
-          if (++frames >= count) {
-            finish();
-            return;
-          }
-          scene.requestRender();
-        });
-        const timer = setTimeout(finish, capMs);
         scene.requestRender();
       });
-  });
+      const timer = setTimeout(() => finish(false), 5000);
+      scene.requestRender();
+    });
+  }, frameCount);
 }
 
 // In-page helper (stringified and re-defined inside each evaluate that needs
@@ -361,21 +280,23 @@ const BEARING_SHIFT_SRC = `
  * @returns {Promise<boolean>} True if tilesLoaded was observed within the timeout.
  */
 function waitForTilesLoaded(page, timeoutMs = 15000) {
-  return waitForPredicate(
+  return page
-    page,
+    .waitForFunction(
-    () => {
+      () => {
-      const scene = window.__godsEyeView.viewer.scene;
+        const scene = window.__godsEyeView.viewer.scene;
-      const prims = scene.primitives;
+        const prims = scene.primitives;
-      for (let i = 0; i < prims.length; i++) {
+        for (let i = 0; i < prims.length; i++) {
-        const p = prims.get(i);
+          const p = prims.get(i);
-        if (p && p.constructor && p.constructor.name === 'Cesium3DTileset') {
+          if (p && p.constructor && p.constructor.name === 'Cesium3DTileset') {
-          return p.tilesLoaded === true;
+            return p.tilesLoaded === true;
+          }
         }
-      }
+        return true; // no tileset in the scene — nothing to wait for
-      return true; // no tileset in the scene — nothing to wait for
+      },
-    },
+      { timeout: timeoutMs },
-    { timeoutMs },
+    )
-  );
+    .then(() => true)
+    .catch(() => false);
 }
 
 /**
@@ -443,10 +364,6 @@ async function main() {
   const chromeExecutable = findChromeExecutable();
   const browser = await puppeteer.launch({
     headless: HEADFUL ? false : 'new',
-    protocolTimeout: PROTOCOL_TIMEOUT_MS,
-    // Talk CDP over a pipe, so no debugging port stays open on localhost for
-    // the length of a headful run.
-    pipe: true,
     ...(chromeExecutable ? { executablePath: chromeExecutable } : {}),
     args: [
       '--no-sandbox',
@@ -480,18 +397,13 @@ async function main() {
     });
     console.log('Loading app...');
     await page.goto(APP_URL, { waitUntil: 'domcontentloaded', timeout: 60000 });
-    const appReady = await waitForPredicate(
+    await page.waitForFunction(
-      page,
       () =>
-        Boolean(
+        window.__godsEyeView &&
-          window.__godsEyeView &&
+        window.__godsEyeView.viewer &&
-          window.__godsEyeView.viewer &&
+        window.__godsEyeView.dataManager,
-          window.__godsEyeView.dataManager,
+      { timeout: 60000 },
-        ),
-      { timeoutMs: 60000 },
     );
-    if (!appReady) throw new Error('app did not initialise within 60s');
-    await installRenderFramesHelper(page);
     // Let the initial fly-to Austin and first tiles settle.
     await sleep(4000);
 
@@ -563,15 +475,18 @@ async function main() {
     console.log(
       `Waiting for geometry-load queue to drain (N=${camCount}, budget ${Math.round(drainBudgetMs / 1000)}s)...`,
     );
-    const drained = await waitForPredicate(
+    const drained = await page
-      page,
+      .waitForFunction(
-      () => {
+        () => {
-        const mod = window.__godsEyeView.dataManager.layers.get('cctv').module;
+          const mod =
-        const ui = mod.getUIState();
+            window.__godsEyeView.dataManager.layers.get('cctv').module;
-        return Boolean(ui.loading) && ui.loading.active === false;
+          const ui = mod.getUIState();
-      },
+          return ui.loading && ui.loading.active === false;
-      { timeoutMs: drainBudgetMs, intervalMs: 1000 },
+        },
-    );
+        { timeout: drainBudgetMs },
+      )
+      .then(() => true)
+      .catch(() => false);
     record(
       `geometry-load queue drains within ${Math.round(drainBudgetMs / 1000)}s (N=${camCount})`,
       drained ? true : HEADFUL ? false : null,
@@ -660,87 +575,27 @@ async function main() {
     // (existence, not just ceiling). The wait below tolerates the update-tick
     // latency of the completion pass (update interval is 10s).
     // -----------------------------------------------------------------------
-    const globeMode = await page.evaluate(
+    console.log('Waiting for tiles + the one-shot completion pass...');
-      () => window.__godsEyeView.viewer.scene.globe?.show !== false,
+    const tilesSeenLoaded = await waitForTilesLoaded(page, 45000);
-    );
+    let sampleFloorOk = false;
-    if (globeMode) {
+    if (tilesSeenLoaded) {
-      // Globe stacks intentionally perform no scene.sampleHeight query.
+      sampleFloorOk = await page
-      // Require independently fetched DEM heights and the actual rendered
+        .waitForFunction(
-      // mount, so a catalog/geoid fallback cannot turn zero samples into a pass.
-      console.log(
-        'Checking terrain-globe completion against live DEM heights...',
-      );
-      const terrain = await page.evaluate(async () => {
-        const camera = window.__godsEyeView.dataManager.layers
-          .get('cctv')
-          .module.getUIState().activeCamera;
-        const exact = `${camera.lon.toFixed(5)},${camera.lat.toFixed(5)}`;
-        const cell = `${camera.lon.toFixed(3)},${camera.lat.toFixed(3)}`;
-        const response = await fetch(
-          `/api/terrain/heights?points=${encodeURIComponent(`${exact};${cell}`)}`,
-          { signal: AbortSignal.timeout(30000) },
-        );
-        const body = await response.json();
-        return { ok: response.ok, results: body.results };
-      });
-      const heights = terrain.results?.map((result) => result?.ellipsoid);
-      const terrainReady =
-        terrain.ok && heights?.length === 2 && heights.every(Number.isFinite);
-      const mountResolved =
-        terrainReady &&
-        (await waitForPredicate(
-          page,
-          (expected, base) => {
-            const { viewer, dataManager } = window.__godsEyeView;
-            const camera = dataManager.layers
-              .get('cctv')
-              .module.getUIState().activeCamera;
-            const ray = viewer.entities.getById(`cctv-${camera.id}-ray-tl`);
-            const mount = ray?.polyline?.positions.getValue(
-              viewer.clock.currentTime,
-            )?.[0];
-            const height =
-              mount &&
-              viewer.scene.globe.ellipsoid.cartesianToCartographic(mount)
-                .height;
-            return (
-              Number.isFinite(camera.groundPriorM) &&
-              Math.abs(camera.groundPriorM - expected[0]) < 0.01 &&
-              Number.isFinite(height) &&
-              expected.some(
-                (ground) =>
-                  Math.abs(height - ground - camera.mountHeightM) < 0.05,
-              ) &&
-              window.__qaCounters.sampleHeight === base
-            );
-          },
-          { timeoutMs: 30000, args: [heights, c0.sampleHeight] },
-        ));
-      record(
-        'terrain-globe completion uses a real DEM height at the rendered mount without mesh samples',
-        Boolean(mountResolved),
-        `terrain=${JSON.stringify(heights)}, mesh sample Δ=${(await readCounters()).sampleHeight - c0.sampleHeight}`,
-      );
-    } else {
-      console.log('Waiting for tiles + the one-shot completion pass...');
-      const tilesSeenLoaded = await waitForTilesLoaded(page, 45000);
-      let sampleFloorOk = false;
-      if (tilesSeenLoaded) {
-        sampleFloorOk = await waitForPredicate(
-          page,
           (base) => window.__qaCounters.sampleHeight - base >= 1,
-          { timeoutMs: 30000, args: [c0.sampleHeight] },
+          { timeout: 30000 },
-        );
+          c0.sampleHeight,
-      }
+        )
-      const cFloor = await readCounters();
+        .then(() => true)
-      record(
+        .catch(() => false);
-        '>=1 real ground sample once tilesLoaded observed (one-shot snap completed)',
-        tilesSeenLoaded ? sampleFloorOk : null,
-        tilesSeenLoaded
-          ? `total real samples since enable=${cFloor.sampleHeight - c0.sampleHeight}`
-          : 'tilesLoaded never observed within 45s — floor not assessable this run',
-      );
     }
+    const cFloor = await readCounters();
+    record(
+      '>=1 real ground sample once tilesLoaded observed (one-shot snap completed)',
+      tilesSeenLoaded ? sampleFloorOk : null,
+      tilesSeenLoaded
+        ? `total real samples since enable=${cFloor.sampleHeight - c0.sampleHeight}`
+        : 'tilesLoaded never observed within 45s — floor not assessable this run',
+    );
 
     // Let the completion pass finish before the steady-state window: require
     // the sampleHeight counter quiet for 12s (> the 10s update interval, so
@@ -1503,7 +1358,18 @@ async function main() {
         },
       });
       window.__qaCctvSiblingOwner = owner;
-      const framesRendered = await window.__qaRenderFrames(3, 10000);
+      await new Promise((resolve) => {
+        let frames = 0;
+        const remove = scene.postRender.addEventListener(() => {
+          if (++frames < 3) {
+            scene.requestRender();
+            return;
+          }
+          remove();
+          resolve();
+        });
+        scene.requestRender();
+      });
       const rect = scene.canvas.getBoundingClientRect();
       const picked = scene.pick(canvasPoint);
       const pickedId = picked?.id?.id ?? picked?.id ?? null;
@@ -1516,33 +1382,26 @@ async function main() {
           typeof pickedId === 'string' ? pickedId : (pickedId?.id ?? null),
         ownerId: owner.id,
         ownsExactObject: picked?.id === owner,
-        framesRendered,
         projectionDelta: Math.hypot(
           projected.x - canvasPoint.x,
           projected.y - canvasPoint.y,
         ),
       };
     }, emptyClickPoint);
-    const siblingOwnsPick =
-      siblingTarget?.pickedId === 'qa-cctv-sibling-owner' &&
-      siblingTarget.ownsExactObject;
-    // No frame at all within the 10s cap points at a stalled renderer rather
-    // than at picking, though the harness can't rule out both. Fail it on the
-    // real-GPU sign-off path; leave it inconclusive under headless GL. A slow
-    // SwiftShader frame (1-2 of 3) still counts as a real miss.
-    const siblingRendererStalled =
-      siblingTarget && !siblingOwnsPick && siblingTarget.framesRendered === 0;
     record(
       'sibling test object owns its canvas pick',
-      !siblingTarget
-        ? null
-        : siblingOwnsPick ||
-            (siblingRendererStalled && !HEADFUL ? null : false),
       siblingTarget
-        ? `${siblingRendererStalled ? 'renderer stalled: ' : ''}frames=${siblingTarget.framesRendered}/3 picked=${siblingTarget.pickedId} exactOwner=${siblingTarget.ownsExactObject} projectionΔ=${siblingTarget.projectionDelta}`
+        ? siblingTarget.pickedId === 'qa-cctv-sibling-owner' &&
+            siblingTarget.ownsExactObject
+        : null,
+      siblingTarget
+        ? `picked=${siblingTarget.pickedId} exactOwner=${siblingTarget.ownsExactObject} projectionΔ=${siblingTarget.projectionDelta}`
         : 'no previously verified empty canvas ray was available',
     );
-    if (siblingOwnsPick) {
+    if (
+      siblingTarget?.pickedId === 'qa-cctv-sibling-owner' &&
+      siblingTarget.ownsExactObject
+    ) {
       await page.mouse.click(siblingTarget.x, siblingTarget.y);
       await sleep(250);
     }
@@ -1567,7 +1426,8 @@ async function main() {
     });
     record(
       'sibling canvas click passes through without CCTV selection or deselection',
-      siblingOwnsPick
+      siblingTarget?.pickedId === 'qa-cctv-sibling-owner' &&
+        siblingTarget.ownsExactObject
         ? siblingClick.activeId === clickEvidenceSetup.activeId &&
             siblingClick.transitions === siblingClick.baselineTransitions &&
             siblingClick.focusEvents === 0 &&
@@ -1766,7 +1626,10 @@ async function main() {
     );
 
     const viewshedShot = path.join(SHOTS_DIR, 'cctv-v3-viewshed.png');
-    await saveReviewShot(page, viewshedShot, 'visual review only');
+    await page.screenshot({ path: viewshedShot });
+    console.log(
+      `  screenshot (visual review only) → ${path.relative(REPO_ROOT, viewshedShot)}`,
+    );
 
     // =========================================================================
     // Group 7: calibration gizmo (v3 design §3c — ADJUST mode + drag)
@@ -1797,34 +1660,6 @@ async function main() {
       gizmoStates.map((s, i) => `${GIZMO_PARTS[i]}=${s}`).join(' '),
     );
 
-    // Frame the actual gizmo for the drag fixture. Default autofocus can leave
-    // its shaft below the 10px interaction threshold; that distant view is not
-    // the drag-usability scenario this regression exercises.
-    const dragFraming = await page.evaluate(async () => {
-      const viewer = window.__godsEyeView.viewer;
-      const e = viewer.entities.getById('cctv-gizmo-move-east');
-      if (!e) return null;
-      const pts = e.polyline.positions.getValue(viewer.clock.currentTime);
-      const target = pts?.[0];
-      if (!target) return null;
-      const measure = () => {
-        const a = viewer.scene.cartesianToCanvasCoordinates(pts[0]);
-        const b = viewer.scene.cartesianToCanvasCoordinates(pts[pts.length - 1]);
-        return {
-          shaftPx: a && b ? Math.hypot(b.x - a.x, b.y - a.y) : null,
-          rangeM: target.constructor.distance(viewer.camera.positionWC, target),
-        };
-      };
-      const before = measure();
-      viewer.camera.cancelFlight();
-      viewer.camera.lookAt(target, new target.constructor(0, -200, 180));
-      viewer.camera.lookAtTransform(viewer.camera.transform.constructor.IDENTITY);
-      viewer.scene.requestRender();
-      const frames = await window.__qaRenderFrames(3, 10000);
-      return { before, after: measure(), frames };
-    });
-    console.log('Drag fixture framing:', JSON.stringify(dragFraming));
-
     // Synthetic CDP drag on the EAST arrow — the owner's field-test
     // regression. Sample effective elevation after every mouse move: it must
     // stay frozen until release, with no transient sampleHeight calls.
@@ -2128,7 +1963,10 @@ async function main() {
     // -----------------------------------------------------------------------
     await sleep(1000);
     const shot = path.join(SHOTS_DIR, 'cctv-v2-active.png');
-    await saveReviewShot(page, shot, 'visual review only, not a gate');
+    await page.screenshot({ path: shot });
+    console.log(
+      `  screenshot (visual review only, not a gate) → ${path.relative(REPO_ROOT, shot)}`,
+    );
 
     // No console errors during the whole exercise.
     record(

scripts/qa-panel-resize.mjs

@@ -298,12 +298,11 @@ async function main() {
     );
     console.log('PASS: header drag lifts CCTV out of the rail');
 
-    // Park above and right of the voice dock and its raised provider chooser:
+    // Park near the top: the voice dock would cover the south corners once
-    // growing every edge must leave the south handles clear of both controls.
+    // the loop below has grown the window.
     {
-      const panel = await readPanel();
       const header = await headerPoint();
-      await drag(header, 900 - panel.left, 120 - header.y);
+      await drag(header, 0, 120 - header.y);
     }
 
     const limits = {

scripts/track-regression.mjs

@@ -2696,9 +2696,9 @@ async function main() {
     // Staged deterministically: park the camera nadir over the synthetic
     // cluster, let rotations settle, TAMPER a billboard's rotation, then
     // trigger each path with the camera idle. The idle-drift catch-up
-    // (ROTATION_REFRESH_MS = 1 s) must not repair a stale first-visible nose
+    // (ROTATION_REFRESH_MS = 1 s) can coincidentally mask a regression in a
-    // before we inspect it: capture that first postRender, with a 250 ms
+    // ~300 ms SwiftShader frame window, so a regression shows as an
-    // deadline that admits the 80 ms fleet cadence without waiting a second.
+    // intermittent (not guaranteed) failure — never a false failure.
     // ============================================================
     console.log('\nChange 4 — arrival rotation: moveEnd settle pass + horizon-reveal pass');
     const arrival = await evalPage(async () => {
@@ -2762,43 +2762,6 @@ async function main() {
       });
       await nextFrames(3);
       const angDiff = (a, b) => Math.abs(Math.atan2(Math.sin(a - b), Math.cos(a - b)));
-      // Render frames are not fleet ticks: at 60/120 Hz four frames can
-      // precede the next 80 ms fleet pass. Observe elapsed time instead, and
-      // freeze the angle on the FIRST visible frame, even when it is wrong.
-      const observeFirstReveal = (bb, course, budgetMs = 250) => new Promise((resolve) => {
-        const startedAt = performance.now();
-        let frames = 0;
-        let settled = false;
-        const finish = (shown, elapsedMs) => {
-          if (settled) return;
-          settled = true;
-          clearTimeout(timer);
-          remove();
-          const expected = shown
-            ? screenProjectedRotation(v.scene, bb.position, course, null)
-            : null;
-          resolve({
-            shown,
-            flipFrame: shown ? frames : -1,
-            revealElapsedMs: elapsedMs,
-            revealWithinBudget: shown && elapsedMs <= budgetMs,
-            dReveal: shown && Number.isFinite(expected) ? angDiff(bb.rotation, expected) : null,
-          });
-        };
-        const remove = v.scene.postRender.addEventListener(() => {
-          frames += 1;
-          const elapsedMs = performance.now() - startedAt;
-          if (bb.show) {
-            finish(true, elapsedMs);
-          } else if (elapsedMs >= budgetMs) {
-            finish(false, elapsedMs);
-          } else {
-            v.scene.requestRender();
-          }
-        });
-        const timer = setTimeout(() => finish(false, performance.now() - startedAt), budgetMs);
-        v.scene.requestRender();
-      });
       const probe = async (id, course) => {
         const bb = findBB(id);
         if (!bb || !bb.show) return { error: `${id} missing/hidden` };
@@ -2816,17 +2779,25 @@ async function main() {
         const expectedMoveEnd = screenProjectedRotation(v.scene, bb.position, course, null);
         // (b) reveal pass: tamper + hide — the next fleet tick must flip it
         // visible AND correct the nose in that same tick (camera still idle,
-        // no moveEnd raised). Record frame count as diagnostics only: the
+        // no moveEnd raised). Diagnostic fields (round 5): record WHICH frame
-        // first visible postRender must already have the corrected rotation.
+        // the flip landed on (flipFrame; -1 = never within the extended
+        // window) and whether a 3D model owns this id — distinguishes "tick
+        // slow under load" from "occluder says hidden" from "model handoff".
         bb.rotation = r0 + 1.5;
         bb.show = false;
-        const reveal = await observeFirstReveal(bb, course);
+        let flipFrame = -1;
+        for (let f = 1; f <= 6; f++) {
+          await nextFrames(1);
+          if (bb.show && flipFrame === -1) flipFrame = f;
+          if (f >= 2 && flipFrame !== -1) break;
+        }
+        const expectedReveal = screenProjectedRotation(v.scene, bb.position, course, null);
         const hasModel = !!(window.__g3dFindModel && window.__g3dFindModel(id));
         return {
           r0,
           dMoveEnd: angDiff(afterMoveEnd, expectedMoveEnd),
-          ...reveal,
+          dReveal: angDiff(bb.rotation, expectedReveal),
-          hasModel,
+          shown: bb.show, flipFrame, hasModel,
         };
       };
       const flightCourse = window.__SYNTH.flights.find((f) => f.icao === 'aaa002')?.track ?? 0;
@@ -2837,18 +2808,20 @@ async function main() {
       };
     });
     const fmtArr = (a) => (!a ? `no result (${arrival?.error || 'phase error'})` : a.error ? a.error
-      : `settle-err=${(a.dMoveEnd * 180 / Math.PI).toFixed(1)}° reveal-err=${a.dReveal === null ? 'unobserved' : (a.dReveal * 180 / Math.PI).toFixed(1) + '°'} shown=${a.shown} flipFrame=${a.flipFrame} revealMs=${a.revealElapsedMs.toFixed(1)} hasModel=${a.hasModel}`);
+      : `settle-err=${(a.dMoveEnd * 180 / Math.PI).toFixed(1)}° reveal-err=${(a.dReveal * 180 / Math.PI).toFixed(1)}° shown=${a.shown} flipFrame=${a.flipFrame} hasModel=${a.hasModel}`);
     const TAMPER_DEG = 1.5 * 180 / Math.PI; // ≈ 86° — an uncorrected nose stays this far off
-    // 250 ms spans multiple 80 ms fleet opportunities while remaining well
+    // Reveal budget re-pinned 2 → 4 frames (round 5): the diagnostic probe
-    // below the 1 s idle catch-up. Never retry until the angle becomes correct:
+    // shows the military flip consistently lands on frame 2 — the exact edge
-    // dReveal is the immutable first-visible-frame observation above.
+    // of the old budget — so any load hiccup flaked it (flights lands frame
+    // 1). The regression this protects against is a reveal that waits for
+    // the 1 s idle catch-up (~30-60 frames) or never re-aims; 4 frames still
+    // catches that with a wide margin, with zero-headroom flakes gone.
     const arrOk = (a) => !!a && !a.error && a.shown
-      && a.revealWithinBudget && a.revealElapsedMs <= 250
+      && (a.flipFrame === -1 ? false : a.flipFrame <= 4)
-      && a.dReveal !== null
       && a.dMoveEnd * 180 / Math.PI < 10 && a.dReveal * 180 / Math.PI < 10;
-    record(`arrival: moveEnd re-aims and first reveal is correct within 250 ms, flights (tamper was ${TAMPER_DEG.toFixed(0)}°)`,
+    record(`arrival: moveEnd + reveal both re-aim within 4 frames, flights (tamper was ${TAMPER_DEG.toFixed(0)}°)`,
       arrOk(arrival.flights), fmtArr(arrival.flights));
-    record(`arrival: moveEnd re-aims and first reveal is correct within 250 ms, military (tamper was ${TAMPER_DEG.toFixed(0)}°)`,
+    record(`arrival: moveEnd + reveal both re-aim within 4 frames, military (tamper was ${TAMPER_DEG.toFixed(0)}°)`,
       arrOk(arrival.military), fmtArr(arrival.military));
 
     // ============================================================

server/providers/cctv.js

@@ -143,7 +143,7 @@ export function cctvProxy({ sourceRoot = process.cwd() } = {}) {
 
         if (url.pathname === '/sources') {
           const body = {
-            trimmedPacks: getCctvSources.trimmedPacks?.(sources) ?? [],
+            trimmedPacks: getCctvSources.trimmedPacks?.() ?? [],
             sources: sources.map((source) => ({
               id: source.id,
               pack: source.pack,

server/providers/cctv/catalog.js

@@ -25,7 +25,6 @@ import {
   loadVegvesenSourcesFromOpenData,
   loadNycSourcesFromOpenData,
   loadTorontoSourcesFromOpenData,
-  loadFloridaSourcesFromOpenData,
 } from './sources.js';
 
 /** Env kill switch: unset or anything but "0" means enabled. */
@@ -145,14 +144,6 @@ const LIVE_PACKS = [
     enabled: () => envOptIn('CCTV_LITHUANIA_ENABLED'),
     load: loadLithuaniaSources,
   },
-  {
-    // FL511's terms limit its content to individual, personal use (other use
-    // needs FDOT's written consent), so the pack is off unless the operator
-    // opts in (see DATA_SOURCES.md).
-    name: 'florida',
-    enabled: () => envOptIn('CCTV_FLORIDA_ENABLED'),
-    load: loadFloridaSourcesFromOpenData,
-  },
 ];
 /**
  * Load CCTV sources from a local JSON file (CCTV_SOURCES_FILE env or default).
@@ -204,19 +195,16 @@ export function createCctvCatalog({ sourceRoot = process.cwd() } = {}) {
   /** @type {Promise<Array<object>>|null} In-flight refresh, shared by concurrent
    * callers so a post-TTL burst launches ONE refetch, not one per request. */
   let _cctvSourceInflight = null;
-  /** @type {WeakMap<Array<object>, Array<{pack: string, available: number, served: number}>>}
+  /** @type {Array<{pack: string, available: number, served: number}>} Packs
-   * Packs that serve fewer cameras than they offer, keyed by the source list
+   * that serve fewer cameras than they offer. */
-   * they describe, so a request served the old list during a background
+  let _cctvTrimmedPacks = [];
-   * refresh never pairs it with the new list's trim notes. */
-  const _cctvTrimmedPacks = new WeakMap();
 
   /**
    * Assemble and cache the merged CCTV source list.
    *
    * Merges every source pack (live open-data packs, local file, env
    * variable), deduplicates by ID, shares the catalog cap fairly across
-   * packs, and caches for CCTV_SOURCE_CACHE_MS. Past that, the cached list is
+   * packs, and caches for CCTV_SOURCE_CACHE_MS.
-   * returned while a background refresh replaces it; only a first load waits.
    *
    * @returns {Promise<Array<object>>} Deduplicated, capped source list.
    */
@@ -231,31 +219,11 @@ export function createCctvCatalog({ sourceRoot = process.cwd() } = {}) {
     // Single-flight: a burst of requests arriving past the TTL shares ONE refresh
     // instead of each launching the full multi-provider refetch. The `.finally`
     // clears the ref so the next post-TTL cycle starts fresh.
-    if (!_cctvSourceInflight) {
+    if (_cctvSourceInflight) return _cctvSourceInflight;
-      _cctvSourceInflight = refreshCctvSources().finally(() => {
+    _cctvSourceInflight = refreshCctvSources().finally(() => {
-        _cctvSourceInflight = null;
+      _cctvSourceInflight = null;
-      });
+    });
-      // A background refresh has no caller waiting on it: report its failure
+    return _cctvSourceInflight;
-      // here, once per refresh rather than once per request it serves. Keep
-      // the old catalog for another TTL, as an empty refresh does, so a refresh
-      // that keeps failing is retried once per TTL, not back to back.
-      if (_cctvSourceCache.length) {
-        _cctvSourceInflight.catch((error) => {
-          _cctvSourceCacheAt = Date.now();
-          console.warn(
-            '[CCTV] background catalog refresh failed; serving',
-            _cctvSourceCache.length,
-            'cameras from the last catalog:',
-            error?.message || error,
-          );
-        });
-      }
-    }
-    // With a catalog in hand, answer with it while the refresh runs: the
-    // refresh lasts as long as the slowest pack (Tarktee's DATEX feeds take up
-    // to its 30 s timeout), and every /api/cctv request would otherwise wait
-    // for it. Only the first load, with nothing to serve yet, waits.
-    return _cctvSourceCache.length ? _cctvSourceCache : _cctvSourceInflight;
   }
 
   /**
@@ -345,7 +313,7 @@ export function createCctvCatalog({ sourceRoot = process.cwd() } = {}) {
     }
     if (capped.length > 0 || _cctvSourceCache.length === 0) {
       _cctvSourceCache = capped;
-      _cctvTrimmedPacks.set(capped, trimmedPacks);
+      _cctvTrimmedPacks = trimmedPacks;
     } else {
       // Every source came back empty (all live packs timed out / upstream outage)
       // but a good catalog is already cached — serve it stale rather than blanking
@@ -359,10 +327,7 @@ export function createCctvCatalog({ sourceRoot = process.cwd() } = {}) {
     return _cctvSourceCache;
   }
 
-  /** Packs serving fewer cameras than they offer in `sources` (by default the
+  /** Packs serving fewer cameras than they offer, as of the last refresh. */
-   * current catalog). Pass the list a request was served to keep the two in
+  getCctvSources.trimmedPacks = () => _cctvTrimmedPacks;
-   * step while a background refresh swaps the catalog. */
-  getCctvSources.trimmedPacks = (sources = _cctvSourceCache) =>
-    _cctvTrimmedPacks.get(sources) ?? [];
   return getCctvSources;
 }

server/providers/cctv/constants.js

@@ -113,34 +113,13 @@ export const CALTRANS_ANCHORS = [
   { lat: 32.7157, lon: -117.1611 }, // San Diego
   { lat: 38.5816, lon: -121.4944 }, // Sacramento
 ];
-export const FLORIDA_CCTV_URL =
-  'https://services.arcgis.com/3wFbqsFPLeKqOlIK/arcgis/rest/services/FL511_Traffic_Cameras/FeatureServer/0/query';
-export const FLORIDA_IMAGE_HOSTS = [
-  'images-dis.divas.cloud',
-  'snapshots.divas.cloud',
-];
-export const DEFAULT_FLORIDA_MAX_SOURCES = 500;
-/** Byte cap per catalog page (2,000 rows, about 650 KiB measured). */
-export const FLORIDA_MAX_CATALOG_BYTES = 2 * 1024 * 1024;
-/** Catalog page ceiling: 40 pages covers 4,000+ cameras even at 100 rows a page. */
-export const FLORIDA_MAX_CATALOG_PAGES = 40;
-export const FLORIDA_ANCHORS = [
-  { lat: 25.7617, lon: -80.1918 }, // Miami
-  { lat: 28.5384, lon: -81.3789 }, // Orlando
-  { lat: 27.9506, lon: -82.4572 }, // Tampa
-  { lat: 30.3322, lon: -81.6557 }, // Jacksonville
-  { lat: 30.4383, lon: -84.2807 }, // Tallahassee
-  { lat: 26.1224, lon: -80.1373 }, // Fort Lauderdale
-  { lat: 26.7153, lon: -80.0534 }, // West Palm Beach
-  { lat: 30.4213, lon: -87.2169 }, // Pensacola (panhandle)
-];
 /** TfL JamCams: one keyless list endpoint; frames live on a public S3 bucket. */
 export const TFL_JAMCAM_URL = 'https://api.tfl.gov.uk/Place/Type/JamCam';
 export const TFL_IMAGE_ORIGIN =
   'https://s3-eu-west-1.amazonaws.com/jamcams.tfl.gov.uk/';
 export const DEFAULT_TFL_MAX_SOURCES = 250;
 export const LONDON_CENTER = { lat: 51.5074, lon: -0.1278 };
-/** Ontario 511: CARS/511 camera catalog, which needs a developer key (ONTARIO_511_API_KEY); frame URLs are still images. */
+/** Ontario 511: keyless CARS/511 camera catalog; frame URLs are still images. */
 export const ONTARIO_511_CAMERAS_URL =
   'https://511on.ca/api/v2/get/cameras?format=json&lang=en';
 export const ONTARIO_511_IMAGE_ORIGIN = 'https://511on.ca/map/Cctv/';
@@ -209,8 +188,6 @@ export const TARKTEE_IMAGES_URL =
   'https://tarktee.transpordiamet.ee/api/v1/datex/roadCameraImages';
 export const TARKTEE_IMAGE_ORIGIN = 'https://tarktee.transpordiamet.ee/images/';
 export const DEFAULT_TARKTEE_MAX_SOURCES = 179;
-/** Hard ceiling per Tarktee DATEX XML document (~120–165 KB live). */
-export const TARKTEE_MAX_CATALOG_BYTES = 4 * 1024 * 1024;
 export const TARKTEE_ANCHORS = [
   { lat: 59.437, lon: 24.753 }, // Tallinn
   { lat: 58.378, lon: 26.729 }, // Tartu
@@ -340,49 +317,6 @@ export const NORWAY_ANCHORS = [
   { lat: 69.6492, lon: 18.9553 }, // Tromsø
 ];
 
-/** Kartverket's keyless point-height API (CC BY 4.0): terrain height above
- * sea level (NN2000), used as the Vegvesen cameras' ground prior because the
- * camera feed's points are 2D. */
-export const KARTVERKET_HEIGHT_URL =
-  'https://ws.geonorge.no/hoydedata/v1/punkt';
-/** Points per request. The API takes up to 50, but above ~20 it answers the
- * extra points from contour lines (`hoydekurver`, metres to ~20 m off) or not
- * at all; at 20 nearly every camera resolves from the 1 m terrain model. */
-export const KARTVERKET_MAX_POINTS = 20;
-/** Requests in flight at once. The whole country is ~36 requests of
- * 0.6-9.5 s each, so a cold lookup takes ~6-13 s. */
-export const KARTVERKET_CONCURRENCY = 8;
-/** Deadline for one complete lookup, shared by every request. A lookup cut
- * short by it is resumed on the next refresh, without a backoff. */
-export const KARTVERKET_LOOKUP_TIMEOUT_MS = 30 * 1000;
-/** One request that takes longer than this counts as a failing service. */
-export const KARTVERKET_REQUEST_TIMEOUT_MS = 10 * 1000;
-/** The Vegvesen lane's budget, measured from the start of the loader (catalog
- * fetch included), for waiting on heights. Under the 15 s per-provider fetch
- * timeout so this pack is never the catalog's slowest lane. A lookup still
- * running after it keeps filling the cache for the next refresh. */
-export const KARTVERKET_CATALOG_WAIT_MS = 12 * 1000;
-/** The lane only waits when more than this share of its cameras has no
- * answer yet (a cold cache). A few new cameras or expired misses are looked
- * up in the background instead of holding the refresh. */
-export const KARTVERKET_WAIT_MISSING_SHARE = 0.1;
-/** A point Kartverket has no height for (some ferry quays and bridges) is not
- * asked about again for this long. */
-export const KARTVERKET_NULL_TTL_MS = 6 * 60 * 60 * 1000;
-/** After a failing request (408, 429, 5xx, a network error, a request
- * timeout or an unreadable body), no lookup starts for this long, or for the
- * Retry-After the service sent, bounded to [1 min, 1 h]. Longer than the
- * 15-minute catalog refresh (CCTV_SOURCE_CACHE_MS), so a failing service
- * costs one attempt per backoff, not one per refresh. */
-export const KARTVERKET_FAILURE_BACKOFF_MS = 30 * 60 * 1000;
-export const KARTVERKET_MAX_BACKOFF_MS = 60 * 60 * 1000;
-export const KARTVERKET_MAX_RESPONSE_BYTES = 256 * 1024;
-/** Plausible Norwegian terrain: below sea level only at the shore, and no road
- * camera sits above ~1,500 m. Anything outside is treated as no height. */
-export const KARTVERKET_HEIGHT_RANGE_M = Object.freeze({ min: -20, max: 2500 });
-/** Same identity the other CCTV upstream requests send. */
-export const KARTVERKET_USER_AGENT = 'gods-eye-view-cctv-proxy/1.0';
-
 /** NYC DOT Traffic Management Center cameras: one keyless JSON list for the
  * five boroughs (~980 cameras). Frames are stills synthesized from each
  * camera UUID on the city's webcam host — never taken from the payload. */
@@ -505,10 +439,6 @@ export const CCTV_SOURCE_CACHE_MS = 15 * 60 * 1000;
  * pending forever — a hung fetch aborts, the loader returns [], and
  * serve-stale/other packs take over. */
 export const CCTV_SOURCE_FETCH_TIMEOUT_MS = 15 * 1000;
-/** Tarktee's two DATEX feeds (120 and 160 KB) answered in 2 to 16.6 s across
- * ten requests on 2026-10-18, so the shared 15 s timeout dropped the Estonian
- * pack on about a third of loads. Both must arrive for any camera to load. */
-export const TARKTEE_FETCH_TIMEOUT_MS = 30 * 1000;
 /** Individual CCTV image fetches must settle before the active 10-second
  * client refresh cadence. A bounded miss can fall through to Street View or
  * the synthetic frame instead of leaving the browser preview pending. */

server/providers/cctv/normalize.js

@@ -377,17 +377,6 @@ export function isLikelyCalgaryCoordinate(lat, lon) {
   );
 }
 
-/** Florida statewide, Key West to Georgia state line, with slack at each edge */
-export function isLikelyFloridaCoordinate(lat, lon) {
-  return (
-    isPlausibleLatLon(lat, lon) &&
-    lat >= 24.3 &&
-    lat <= 31.1 &&
-    lon >= -87.7 &&
-    lon <= -79.8
-  );
-}
-
 /** New York City's five boroughs, with slack for the harbor and city line. */
 export function isLikelyNycCoordinate(lat, lon) {
   return (

server/providers/cctv/ontario511.test.mjs

@@ -1,169 +0,0 @@
-import assert from 'node:assert/strict';
-import test from 'node:test';
-
-import {
-  _resetOntarioKeyWarningForTest,
-  loadOntarioSourcesFromOpenData,
-} from './sources.js';
-
-const ROW = {
-  Id: '42',
-  Latitude: 43.6532,
-  Longitude: -79.3832,
-  Location: 'Hwy 401 near Yonge St',
-  Direction: 'Eastbound',
-  Views: [
-    {
-      Status: 'Enabled',
-      Url: 'https://511on.ca/map/Cctv/4201',
-      Description: 'Eastbound',
-    },
-  ],
-};
-
-function captureConsole(t) {
-  const lines = [];
-  const capture = (...args) => lines.push(args.join(' '));
-  t.mock.method(console, 'warn', capture);
-  t.mock.method(console, 'log', capture);
-  return lines;
-}
-
-test.beforeEach(() => _resetOntarioKeyWarningForTest());
-
-test('without ONTARIO_511_API_KEY the Ontario pack is skipped, logged once', async (t) => {
-  const lines = captureConsole(t);
-  let fetches = 0;
-  t.mock.method(globalThis, 'fetch', async () => {
-    fetches += 1;
-    return Response.json([ROW]);
-  });
-  assert.deepEqual(await loadOntarioSourcesFromOpenData({}, {}), []);
-  assert.deepEqual(
-    await loadOntarioSourcesFromOpenData({}, { ONTARIO_511_API_KEY: '   ' }),
-    [],
-  );
-  assert.equal(fetches, 0);
-  assert.equal(lines.length, 1);
-  assert.match(lines[0], /ONTARIO_511_API_KEY/);
-});
-
-test('with a key the camera list is requested with it and parsed', async (t) => {
-  const lines = captureConsole(t);
-  const requested = [];
-  t.mock.method(globalThis, 'fetch', async (url) => {
-    requested.push(String(url));
-    return Response.json([ROW]);
-  });
-  const cameras = await loadOntarioSourcesFromOpenData(
-    { sourceRoot: '/ignored' },
-    { ONTARIO_511_API_KEY: ' test-key ' },
-  );
-  assert.equal(requested.length, 1);
-  const url = new URL(requested[0]);
-  assert.equal(url.host, '511on.ca');
-  assert.equal(url.searchParams.get('key'), 'test-key');
-  assert.equal(url.searchParams.get('format'), 'json');
-  assert.equal(cameras.length, 1);
-  assert.equal(cameras[0].id, 'on-42');
-  assert.equal(cameras[0].url, 'https://511on.ca/map/Cctv/4201');
-  // The records go to the browser through /api/cctv; the key must stay on
-  // the server-side catalog request.
-  assert.doesNotMatch(JSON.stringify(cameras), /test-key/);
-  assert.doesNotMatch(lines.join('\n'), /test-key/);
-});
-
-test('the source cap is read from the same environment as the key', async (t) => {
-  captureConsole(t);
-  const rows = Array.from({ length: 12 }, (_, i) => ({
-    ...ROW,
-    Id: String(100 + i),
-    Latitude: ROW.Latitude + i * 0.01,
-    Views: [{ ...ROW.Views[0], Url: `https://511on.ca/map/Cctv/${100 + i}` }],
-  }));
-  t.mock.method(globalThis, 'fetch', async () => Response.json(rows));
-  const cameras = await loadOntarioSourcesFromOpenData(
-    {},
-    { ONTARIO_511_API_KEY: 'test-key', CCTV_ONTARIO_MAX_SOURCES: '8' },
-  );
-  assert.equal(cameras.length, 8);
-});
-
-for (const status of [400, 401, 403]) {
-  test(`a ${status} points at the key by name, never by value`, async (t) => {
-    const lines = captureConsole(t);
-    t.mock.method(globalThis, 'fetch', async () =>
-      Response.json({ Message: 'Invalid Key' }, { status }),
-    );
-    const cameras = await loadOntarioSourcesFromOpenData(
-      {},
-      { ONTARIO_511_API_KEY: 'secret-key-value' },
-    );
-    assert.deepEqual(cameras, []);
-    assert.match(
-      lines.join('\n'),
-      new RegExp(`failed: ${status} \\(check ONTARIO_511_API_KEY\\)`),
-    );
-    assert.doesNotMatch(lines.join('\n'), /secret-key-value/);
-  });
-}
-
-for (const status of [429, 500, 503]) {
-  test(`a ${status} is reported without blaming the key`, async (t) => {
-    const lines = captureConsole(t);
-    t.mock.method(globalThis, 'fetch', async () =>
-      Response.json({}, { status }),
-    );
-    const cameras = await loadOntarioSourcesFromOpenData(
-      {},
-      { ONTARIO_511_API_KEY: 'secret-key-value' },
-    );
-    assert.deepEqual(cameras, []);
-    assert.equal(lines.length, 1);
-    assert.equal(
-      lines[0],
-      `[CCTV] Ontario 511 camera download failed: ${status}`,
-    );
-    assert.doesNotMatch(lines[0], /secret-key-value/);
-  });
-}
-
-for (const failure of ['transport', 'invalid-json']) {
-  test(`Ontario ${failure} failures cannot log reflected keys or request URLs`, async (t) => {
-    const lines = captureConsole(t);
-    const key = 'synthetic secret&/=%value';
-    t.mock.method(globalThis, 'fetch', async (url) => {
-      if (failure === 'transport')
-        throw new Error(`request failed: ${url} ${key}`);
-      return new Response(`not JSON: ${url} ${key}`);
-    });
-    assert.deepEqual(
-      await loadOntarioSourcesFromOpenData({}, { ONTARIO_511_API_KEY: key }),
-      [],
-    );
-    assert.equal(lines.length, 1);
-    assert.match(lines[0], /Ontario 511 camera download error/);
-    assert.equal(lines[0].includes(key), false);
-    assert.equal(lines[0].includes('synthetic'), false);
-    assert.equal(lines[0].includes('https://'), false);
-  });
-}
-
-test('Ontario encodes reserved key characters and refuses credential-bearing redirects', async (t) => {
-  const lines = captureConsole(t);
-  const key = 'synthetic &/=% value';
-  let request;
-  t.mock.method(globalThis, 'fetch', async (url, init) => {
-    request = { url: new URL(url), init };
-    return Response.json([ROW]);
-  });
-  const cameras = await loadOntarioSourcesFromOpenData(
-    {},
-    { ONTARIO_511_API_KEY: key },
-  );
-  assert.equal(request.url.searchParams.get('key'), key);
-  assert.equal(request.init.redirect, 'error');
-  assert.equal(cameras.length, 1);
-  assert.equal(JSON.stringify(cameras).includes('synthetic'), false);
-  assert.equal(lines.join(' ').includes('synthetic'), false);
-});

server/providers/cctv/sources.js

@@ -42,8 +42,6 @@ import {
   TARKTEE_IMAGES_URL,
   TARKTEE_IMAGE_ORIGIN,
   DEFAULT_TARKTEE_MAX_SOURCES,
-  TARKTEE_MAX_CATALOG_BYTES,
-  TARKTEE_FETCH_TIMEOUT_MS,
   TARKTEE_ANCHORS,
   DEFAULT_WARENDORF_SOURCE_FILE,
   WARENDORF_IMAGE_ORIGINS,
@@ -57,12 +55,6 @@ import {
   DEFAULT_CALGARY_MAX_SOURCES,
   CALGARY_DOWNTOWN,
   CALGARY_MAX_CATALOG_BYTES,
-  FLORIDA_CCTV_URL,
-  FLORIDA_IMAGE_HOSTS,
-  DEFAULT_FLORIDA_MAX_SOURCES,
-  FLORIDA_ANCHORS,
-  FLORIDA_MAX_CATALOG_BYTES,
-  FLORIDA_MAX_CATALOG_PAGES,
   CATALONIA_CAMERAS_URL,
   CATALONIA_MAX_CATALOG_BYTES,
   CATALONIA_IMAGE_HOSTS,
@@ -97,19 +89,6 @@ import {
   DEFAULT_VEGVESEN_MAX_SOURCES,
   VEGVESEN_MAX_CATALOG_BYTES,
   NORWAY_ANCHORS,
-  KARTVERKET_HEIGHT_URL,
-  KARTVERKET_MAX_POINTS,
-  KARTVERKET_CONCURRENCY,
-  KARTVERKET_LOOKUP_TIMEOUT_MS,
-  KARTVERKET_REQUEST_TIMEOUT_MS,
-  KARTVERKET_WAIT_MISSING_SHARE,
-  KARTVERKET_CATALOG_WAIT_MS,
-  KARTVERKET_NULL_TTL_MS,
-  KARTVERKET_FAILURE_BACKOFF_MS,
-  KARTVERKET_MAX_BACKOFF_MS,
-  KARTVERKET_USER_AGENT,
-  KARTVERKET_MAX_RESPONSE_BYTES,
-  KARTVERKET_HEIGHT_RANGE_M,
   NYC_CAMERAS_URL,
   NYC_IMAGE_URL,
   NYC_CAMERA_ID_RE,
@@ -134,7 +113,6 @@ import {
   isLikelyTexasCoordinate,
   isLikelyNswCoordinate,
   isLikelyCalgaryCoordinate,
-  isLikelyFloridaCoordinate,
   isLikelyCataloniaCoordinate,
   decodeNumericEntities,
   isLikelyNycCoordinate,
@@ -524,57 +502,22 @@ function pickOntarioCctvView(views) {
   );
 }
 
-let ontarioKeyMissingLogged = false;
-
-/** Test seam: let the next keyless call log the missing-key line again. */
-export function _resetOntarioKeyWarningForTest() {
-  ontarioKeyMissingLogged = false;
-}
-
 /**
- * Fetch Ontario 511 CCTV cameras. The camera list comes from the 511 API,
+ * Fetch Ontario 511 CCTV cameras. Keyless: the catalog is exposed by the
- * which now requires a free developer key (511on.ca/developers/doc, "Requires a
+ * public 511 API, while frame URLs are stable still-image endpoints under
- * developer key"; unkeyed calls answer 400 "Invalid Key"), read from
+ * 511on.ca/map/Cctv/. Only rows with finite Ontario coords and at least one
- * ONTARIO_511_API_KEY. Without one the pack is skipped with a single log line.
+ * enabled official still view are kept.
- * Frame URLs are stable still-image endpoints under 511on.ca/map/Cctv/. Only
- * rows with finite Ontario coords and at least one enabled official still
- * view are kept.
  *
- * @param {object} [_options] The catalog's loader options (unused).
- * @param {object} [env] Environment to read the key and the source cap from.
  * @returns {Promise<Array<object>>} Normalized camera source objects.
  */
-export async function loadOntarioSourcesFromOpenData(
+export async function loadOntarioSourcesFromOpenData() {
-  _options = {},
-  env = process.env,
-) {
-  const key = String(env.ONTARIO_511_API_KEY ?? '').trim();
-  if (!key) {
-    if (!ontarioKeyMissingLogged) {
-      ontarioKeyMissingLogged = true;
-      console.warn(
-        '[CCTV] Ontario 511 cameras skipped: the 511on.ca API needs a free developer key (set ONTARIO_511_API_KEY)',
-      );
-    }
-    return [];
-  }
   try {
-    const url = new URL(ONTARIO_511_CAMERAS_URL);
+    const resp = await fetch(ONTARIO_511_CAMERAS_URL, {
-    url.searchParams.set('key', key);
-    const resp = await fetch(url, {
       headers: { Accept: 'application/json' },
-      redirect: 'error',
       signal: AbortSignal.timeout(CCTV_SOURCE_FETCH_TIMEOUT_MS),
     });
     if (!resp.ok) {
-      // The API answers 400 "Invalid Key" to a wrong or revoked key.
+      console.warn('[CCTV] Ontario 511 camera download failed:', resp.status);
-      const keyHint =
-        resp.status === 400 || resp.status === 401 || resp.status === 403
-          ? ' (check ONTARIO_511_API_KEY)'
-          : '';
-      console.warn(
-        `[CCTV] Ontario 511 camera download failed: ${resp.status}${keyHint}`,
-      );
       return [];
     }
     const rows = await resp.json();
@@ -637,7 +580,7 @@ export async function loadOntarioSourcesFromOpenData(
       new Map(cameras.map((camera) => [camera.id, camera])).values(),
     );
     const maxRaw = Number(
-      env.CCTV_ONTARIO_MAX_SOURCES || DEFAULT_ONTARIO_MAX_SOURCES,
+      process.env.CCTV_ONTARIO_MAX_SOURCES || DEFAULT_ONTARIO_MAX_SOURCES,
     );
     const maxCount = Number.isFinite(maxRaw)
       ? Math.max(8, Math.min(1000, Math.floor(maxRaw)))
@@ -647,11 +590,10 @@ export async function loadOntarioSourcesFromOpenData(
       `[CCTV] Loaded Ontario 511 camera sources: ${unique.length} enabled (using nearest ${prioritized.length})`,
     );
     return prioritized;
-  } catch {
+  } catch (error) {
-    // Transport and JSON errors may reflect the credential-bearing request.
-    // Do not log upstream exception text, response bodies or URLs.
     console.warn(
-      '[CCTV] Ontario 511 camera download error (network or invalid response)',
+      '[CCTV] Ontario 511 camera download error:',
+      error?.message || error,
     );
     return [];
   }
@@ -1248,49 +1190,28 @@ export function parseTarkteeDatexImages(xml) {
  * @returns {Promise<Array<object>>} Normalized camera source objects.
  */
 export async function loadTarkteeSourcesFromDatex() {
-  // Own both transports before either can reject. A response that arrives
-  // after cleanup must also be discarded instead of escaping Promise.all.
-  const abort = new AbortController();
-  const signal = AbortSignal.any([
-    abort.signal,
-    AbortSignal.timeout(TARKTEE_FETCH_TIMEOUT_MS),
-  ]);
-  const responses = [];
-  const discardBoth = async () => {
-    abort.abort();
-    await Promise.allSettled(
-      responses.map((response) => response.body?.cancel()),
-    );
-    return [];
-  };
-  const fetchXml = async (url) => {
-    const response = await fetch(url, {
-      headers: { Accept: 'application/xml,text/xml,*/*' },
-      redirect: 'manual',
-      signal,
-    });
-    if (signal.aborted) {
-      await Promise.allSettled([response.body?.cancel()]);
-      signal.throwIfAborted();
-    }
-    responses.push(response);
-    if (!response.ok) {
-      throw new Error(
-        response.status >= 300 && response.status < 400
-          ? 'catalog redirected; redirects are not followed'
-          : `catalog HTTP ${response.status}`,
-      );
-    }
-    return response;
-  };
   try {
     const [locResp, imgResp] = await Promise.all([
-      fetchXml(TARKTEE_LOCATIONS_URL),
+      fetch(TARKTEE_LOCATIONS_URL, {
-      fetchXml(TARKTEE_IMAGES_URL),
+        headers: { Accept: 'application/xml,text/xml,*/*' },
+        signal: AbortSignal.timeout(CCTV_SOURCE_FETCH_TIMEOUT_MS),
+      }),
+      fetch(TARKTEE_IMAGES_URL, {
+        headers: { Accept: 'application/xml,text/xml,*/*' },
+        signal: AbortSignal.timeout(CCTV_SOURCE_FETCH_TIMEOUT_MS),
+      }),
     ]);
+    if (!locResp.ok) {
+      console.warn('[CCTV] Tarktee locations download failed:', locResp.status);
+      return [];
+    }
+    if (!imgResp.ok) {
+      console.warn('[CCTV] Tarktee images download failed:', imgResp.status);
+      return [];
+    }
     const [locXml, imgXml] = await Promise.all([
-      readResponseTextCapped(locResp, TARKTEE_MAX_CATALOG_BYTES, signal),
+      locResp.text(),
-      readResponseTextCapped(imgResp, TARKTEE_MAX_CATALOG_BYTES, signal),
+      imgResp.text(),
     ]);
     const locations = parseTarkteeDatexLocations(locXml);
     const images = parseTarkteeDatexImages(imgXml);
@@ -1303,7 +1224,6 @@ export async function loadTarkteeSourcesFromDatex() {
     }
 
     const cameras = [];
-    const seen = new Set();
     for (const [locationId, loc] of locations.entries()) {
       const imageUrl = images.get(locationId);
       if (!imageUrl) continue;
@@ -1315,8 +1235,6 @@ export async function loadTarkteeSourcesFromDatex() {
       const cameraId = numMatch
         ? `ee-tarktee-${numMatch[1]}`
         : `ee-tarktee-${locationId}`;
-      if (seen.has(cameraId)) continue;
-      seen.add(cameraId);
       cameras.push({
         id: cameraId,
         name: loc.name,
@@ -1352,7 +1270,6 @@ export async function loadTarkteeSourcesFromDatex() {
     );
     return prioritized;
   } catch (error) {
-    await discardBoth();
     console.warn(
       '[CCTV] Tarktee DATEX download error:',
       error?.message || error,
@@ -2469,11 +2386,14 @@ export function vegvesenCameraToSource(feature) {
     fovDeg: 44,
     rangeM: 145,
     mountHeightM: 8,
-    // The feed's coordinates are 2D. The loader replaces this flat prior with
+    // KNOWN LIMITATION: the feed's coordinates are 2D, so this is one flat
-    // Kartverket's terrain height for each camera (applyVegvesenGroundHeights);
+    // prior for the whole country, while cameras run from sea level to
-    // it only survives when that lookup fails, and then a mountain-pass camera
+    // mountain passes near 1,000 m (Haukelifjell, Sjonfjellet, Rugeldalen).
-    // can sit below the terrain on a stack without 3D tiles, the same risk the
+    // The point-height prior and the client's one-shot ground snap correct it
-    // Caltrans pack documents.
+    // where they resolve; on a stack where neither does (no 3D tiles), a pass
+    // camera stays hundreds of metres below the terrain, the same risk the
+    // Caltrans pack documents. A per-camera height (e.g. Kartverket's keyless
+    // point-height API) would remove it.
     groundElevationM: 150,
     feedType: videoUrl ? 'hls' : 'image',
     url: videoUrl || imageUrl,
@@ -2493,7 +2413,6 @@ export function vegvesenCameraToSource(feature) {
  * @returns {Promise<Array<object>>} Normalized camera source objects.
  */
 export async function loadVegvesenSourcesFromOpenData() {
-  const startedAt = Date.now();
   try {
     const endpoint = process.env.CCTV_VEGVESEN_URL || DEFAULT_VEGVESEN_CCTV_URL;
     const resp = await fetch(endpoint, {
@@ -2539,12 +2458,6 @@ export async function loadVegvesenSourcesFromOpenData() {
       ? Math.max(8, Math.min(1000, Math.floor(maxRaw)))
       : DEFAULT_VEGVESEN_MAX_SOURCES;
     const prioritized = prioritizeSources(cameras, maxCount, NORWAY_ANCHORS);
-    await applyVegvesenGroundHeights(prioritized, {
-      waitMs: Math.max(
-        0,
-        KARTVERKET_CATALOG_WAIT_MS - (Date.now() - startedAt),
-      ),
-    });
     console.log(
       `[CCTV] Loaded Vegvesen camera sources: ${cameras.length} (using nearest ${prioritized.length})`,
     );
@@ -2558,322 +2471,6 @@ export async function loadVegvesenSourcesFromOpenData() {
   }
 }
 
-/**
- * Kartverket answers by rounded position: `{z, expires}`, where z is metres or
- * null for "no height there". Heights never expire (camera positions barely
- * change); nulls expire after KARTVERKET_NULL_TTL_MS. The 15-minute catalog
- * refresh therefore only asks about new or moved cameras. Bounded well above
- * the ~900 cameras the pack can load.
- */
-const kartverketHeightCache = new Map();
-const KARTVERKET_CACHE_LIMIT = 5000;
-/** The lookup in flight, so overlapping catalog loads never start a second. */
-let kartverketPending = null;
-/** No lookup starts before this time (epoch ms) after a transport failure. */
-let kartverketBackoffUntil = 0;
-/** Bumped by clearKartverketHeightCache, so a lookup started before a clear
- * can no longer write to the cache, the backoff or the pending slot. */
-let kartverketGeneration = 0;
-
-/** Cache key for one position, at the ~0.1 m precision the request sends. */
-const kartverketKey = (lon, lat) => `${lon.toFixed(6)},${lat.toFixed(6)}`;
-
-/** Statuses that say the service, not the request, is failing. */
-const isKartverketTransportStatus = (status) =>
-  status === 408 || status === 429 || status >= 500;
-
-/** Forget cached heights, the backoff and any lookup in flight. Tests only. */
-export function clearKartverketHeightCache() {
-  kartverketGeneration += 1;
-  kartverketHeightCache.clear();
-  kartverketPending = null;
-  kartverketBackoffUntil = 0;
-}
-
-/**
- * How long to back off after a failed request: the Retry-After the service
- * sent (seconds or an HTTP date), else the default, bounded to [1 min, 1 h].
- *
- * @param {?string} retryAfter - The Retry-After header, if any.
- * @param {number} now - Epoch ms.
- * @returns {number} Milliseconds.
- */
-export function kartverketBackoffMs(retryAfter, now = Date.now()) {
-  let ms = KARTVERKET_FAILURE_BACKOFF_MS;
-  const text = String(retryAfter ?? '').trim();
-  if (/^\d+$/.test(text)) ms = Number(text) * 1000;
-  else if (text && Number.isFinite(Date.parse(text))) {
-    ms = Date.parse(text) - now;
-  }
-  return Math.max(60 * 1000, Math.min(KARTVERKET_MAX_BACKOFF_MS, ms));
-}
-
-/**
- * Terrain heights above sea level (NN2000) from Kartverket's keyless
- * point-height API, KARTVERKET_MAX_POINTS points per request. Each answer is
- * matched back by the coordinates the API echoes, and only for points that
- * request asked about, then reported through `into.set(key, z)` as its
- * request lands, so a caller that stops waiting keeps what has arrived. `z` is
- * metres, or null when the API has no usable height there. A point a 200
- * answer leaves out is reported as null too, so it is not asked again on
- * every refresh.
- *
- * Over water `/punkt` returns the depth of the sea floor (`datakilde:
- * dybdekurver`, `terreng: Havflate`; −547 m under Nordhordlandsbrua). Either
- * marker counts as 0 m, the water surface. For the ~14 bridge cameras that is
- * below the deck, but far closer than the sea floor or a flat prior.
- *
- * The first transport failure (a 408, 429 or 5xx, a network error, a request
- * past KARTVERKET_REQUEST_TIMEOUT_MS, an unreadable or oversized body, or the
- * shared deadline) stops the lookup: no further requests start, and the
- * failure is returned so the caller can back off. Points in failed requests
- * are not reported, so they are asked again later. Any other 4xx rejects that
- * request's points, not the service: they are reported as null and the lookup
- * carries on.
- *
- * @param {Array<{lon:number, lat:number}>} points
- * @param {{into?: {set: Function}, timeoutMs?: number, requestTimeoutMs?: number}} [options]
- * @returns {Promise<{heights: Map<string, ?number>, failure: ?{status: ?number, retryAfter: ?string, deadline: boolean}}>}
- *   `heights` is `into` when it is a Map, else a Map of what was reported.
- *   `failure.deadline` is true when only the shared deadline ran out.
- */
-export async function fetchKartverketHeights(
-  points,
-  {
-    into = new Map(),
-    timeoutMs = KARTVERKET_LOOKUP_TIMEOUT_MS,
-    requestTimeoutMs = KARTVERKET_REQUEST_TIMEOUT_MS,
-  } = {},
-) {
-  const heights = into instanceof Map ? into : new Map();
-  const report = (key, z) => {
-    if (heights !== into) heights.set(key, z);
-    into.set(key, z);
-  };
-  const unique = Array.from(
-    new Map(
-      (points || [])
-        .filter((p) => isLikelyNorwayCoordinate(p?.lat, p?.lon))
-        .map((p) => [kartverketKey(p.lon, p.lat), p]),
-    ).values(),
-  );
-  let failure = null;
-  if (!unique.length) return { heights, failure };
-  const batches = [];
-  for (let i = 0; i < unique.length; i += KARTVERKET_MAX_POINTS) {
-    batches.push(unique.slice(i, i + KARTVERKET_MAX_POINTS));
-  }
-  const deadline = AbortSignal.timeout(timeoutMs);
-  const fetchBatch = async (batch) => {
-    const asked = new Set(batch.map((p) => kartverketKey(p.lon, p.lat)));
-    const url = new URL(KARTVERKET_HEIGHT_URL);
-    url.searchParams.set(
-      'punkter',
-      JSON.stringify(
-        batch.map((p) => [Number(p.lon.toFixed(6)), Number(p.lat.toFixed(6))]),
-      ),
-    );
-    url.searchParams.set('koordsys', '4258');
-    const resp = await fetch(url, {
-      headers: {
-        Accept: 'application/json',
-        'User-Agent': KARTVERKET_USER_AGENT,
-      },
-      redirect: 'error',
-      signal: AbortSignal.any([
-        deadline,
-        AbortSignal.timeout(requestTimeoutMs),
-      ]),
-    });
-    if (!resp.ok) {
-      try {
-        await resp.body?.cancel();
-      } catch {
-        /* no-op */
-      }
-      if (!isKartverketTransportStatus(resp.status)) {
-        console.warn(
-          `[CCTV] Kartverket rejected ${asked.size} points: HTTP ${resp.status}`,
-        );
-        for (const key of asked) report(key, null);
-        return;
-      }
-      const error = new Error(`HTTP ${resp.status}`);
-      error.status = resp.status;
-      error.retryAfter = resp.headers.get('retry-after');
-      throw error;
-    }
-    const payload = await readResponseJsonCapped(
-      resp,
-      KARTVERKET_MAX_RESPONSE_BYTES,
-    );
-    for (const point of Array.isArray(payload?.punkter)
-      ? payload.punkter
-      : []) {
-      const x = toFiniteNumber(point?.x);
-      const y = toFiniteNumber(point?.y);
-      if (!Number.isFinite(x) || !Number.isFinite(y)) continue;
-      const key = kartverketKey(x, y);
-      // Only the points this request asked about: an odd answer can neither
-      // grow the cache nor overwrite another camera.
-      if (!asked.has(key)) continue;
-      asked.delete(key);
-      // `z: null` means no height there; Number(null) would read 0.
-      const raw = point?.z;
-      let z =
-        raw === null || raw === undefined || raw === ''
-          ? NaN
-          : toFiniteNumber(raw);
-      if (
-        Number.isFinite(z) &&
-        (point?.datakilde === 'dybdekurver' || point?.terreng === 'Havflate')
-      ) {
-        z = 0;
-      }
-      const usable =
-        Number.isFinite(z) &&
-        z >= KARTVERKET_HEIGHT_RANGE_M.min &&
-        z <= KARTVERKET_HEIGHT_RANGE_M.max;
-      report(key, usable ? z : null);
-    }
-    // A 200 that leaves a point out has no height for it either.
-    for (const key of asked) report(key, null);
-  };
-  let next = 0;
-  const worker = async () => {
-    while (next < batches.length && !failure) {
-      const batch = batches[next++];
-      try {
-        await fetchBatch(batch);
-      } catch (error) {
-        if (!failure) {
-          failure = {
-            status: Number.isFinite(error?.status) ? error.status : null,
-            retryAfter: error?.retryAfter ?? null,
-            deadline: deadline.aborted,
-          };
-          console.warn(
-            '[CCTV] Kartverket height lookup failed:',
-            error?.message || error,
-          );
-        }
-      }
-    }
-  };
-  await Promise.all(
-    Array.from(
-      { length: Math.min(KARTVERKET_CONCURRENCY, batches.length) },
-      worker,
-    ),
-  );
-  return { heights, failure };
-}
-
-/**
- * Give each Vegvesen camera its own terrain height as the ground prior, in
- * place. Waits at most `waitMs` for positions it has no answer for, and only
- * when more than KARTVERKET_WAIT_MISSING_SHARE of the cameras are missing
- * (a cold cache); a few new cameras or expired misses are looked up in the
- * background. A lookup still running when the wait ends keeps filling the
- * cache for the next catalog refresh. Cameras without a height keep the flat
- * prior. After a transport failure no lookup starts until the backoff ends,
- * which outlasts the 15-minute catalog refresh, so a failing Kartverket costs
- * one attempt per backoff, not one per refresh. A lookup cut short only by its
- * shared deadline is resumed on the next refresh without a backoff. Cameras
- * without finite coordinates are skipped. Never throws.
- * CCTV_VEGVESEN_HEIGHTS=0 turns it off.
- *
- * @param {Array<object>} cameras - Sources from vegvesenCameraToSource().
- * @param {{waitMs?: number, now?: () => number, timeoutMs?: number}} [options]
- *   `timeoutMs` is the lookup's shared deadline.
- * @returns {Promise<number>} How many cameras got a terrain height.
- */
-export async function applyVegvesenGroundHeights(
-  cameras,
-  {
-    waitMs = KARTVERKET_CATALOG_WAIT_MS,
-    now = Date.now,
-    timeoutMs = KARTVERKET_LOOKUP_TIMEOUT_MS,
-  } = {},
-) {
-  if (String(process.env.CCTV_VEGVESEN_HEIGHTS || '1').trim() === '0') return 0;
-  const list = (Array.isArray(cameras) ? cameras : []).filter(
-    (c) => Number.isFinite(c?.lon) && Number.isFinite(c?.lat),
-  );
-  const startedAt = now();
-  const missing = list.filter((c) => {
-    const entry = kartverketHeightCache.get(kartverketKey(c.lon, c.lat));
-    return !entry || entry.expires <= startedAt;
-  });
-  if (
-    missing.length &&
-    !kartverketPending &&
-    startedAt >= kartverketBackoffUntil
-  ) {
-    if (kartverketHeightCache.size + missing.length > KARTVERKET_CACHE_LIMIT) {
-      kartverketHeightCache.clear();
-    }
-    const generation = kartverketGeneration;
-    const current = () => generation === kartverketGeneration;
-    const sink = {
-      set: (key, z) => {
-        if (!current()) return;
-        kartverketHeightCache.set(key, {
-          z,
-          expires: z === null ? now() + KARTVERKET_NULL_TTL_MS : Infinity,
-        });
-      },
-    };
-    const pending = fetchKartverketHeights(missing, { into: sink, timeoutMs })
-      .then(({ failure }) => {
-        if (failure && !failure.deadline && current()) {
-          kartverketBackoffUntil =
-            now() + kartverketBackoffMs(failure.retryAfter, now());
-        }
-      })
-      .catch((error) => {
-        if (current()) {
-          kartverketBackoffUntil = now() + KARTVERKET_FAILURE_BACKOFF_MS;
-        }
-        console.warn(
-          '[CCTV] Kartverket height lookup error:',
-          error?.message || error,
-        );
-      })
-      .finally(() => {
-        if (kartverketPending === pending) kartverketPending = null;
-      });
-    kartverketPending = pending;
-  }
-  const cold = missing.length > list.length * KARTVERKET_WAIT_MISSING_SHARE;
-  if (cold && kartverketPending && waitMs > 0) {
-    let timer;
-    await Promise.race([
-      kartverketPending,
-      new Promise((resolve) => {
-        timer = setTimeout(resolve, waitMs);
-        timer.unref?.();
-      }),
-    ]);
-    clearTimeout(timer);
-  }
-  let applied = 0;
-  for (const camera of list) {
-    const z = kartverketHeightCache.get(
-      kartverketKey(camera.lon, camera.lat),
-    )?.z;
-    if (!Number.isFinite(z)) continue;
-    camera.groundElevationM = Math.round(z * 10) / 10;
-    applied += 1;
-  }
-  if (list.length) {
-    console.log(
-      `[CCTV] Kartverket ground heights: ${applied}/${list.length} Vegvesen cameras`,
-    );
-  }
-  return applied;
-}
-
 const NYC_BOROUGHS = new Set([
   'Manhattan',
   'Brooklyn',
@@ -3187,203 +2784,3 @@ export async function loadTorontoSourcesFromOpenData() {
     return [];
   }
 }
-
-/** FL511 DIRECTION codes as headings; "NOT DIRECTIONAL" has none. */
-const FLORIDA_DIRECTION_HEADINGS = Object.freeze({
-  N: 0,
-  E: 90,
-  S: 180,
-  W: 270,
-});
-
-/**
- * Stable camera id from a frame URL. FL511's ID column repeats across regions
- * (ID 1220 is both an I-75 and an I-95 camera), so the image channel is the
- * key, as Calgary keys on its frame filename. Falls back to a path slug.
- *
- * @param {string} imageUrl - A host-pinned FL511 frame URL.
- * @returns {?string} Provider-stable id, or null when underivable.
- */
-export function floridaCameraId(imageUrl) {
-  let path;
-  try {
-    path = new URL(String(imageUrl ?? '')).pathname;
-  } catch {
-    return null;
-  }
-  const channel = /\/chan-(\d+)_[a-z]+\.jpg$/i.exec(path);
-  if (channel) return `fl-${channel[1]}`;
-  const slug = path
-    .replace(/^\/+|\.[a-z0-9]+$/gi, '')
-    .replace(/[^a-zA-Z0-9]+/g, '-')
-    .toLowerCase();
-  return slug ? `fl-${slug}` : null;
-}
-
-/**
- * One FL511 ArcGIS feature -> one catalog source, or null. DIRECTION is a
- * one-letter code the free-text parser won't read, so a table maps it.
- *
- * @param {object} feature - ArcGIS feature from the FL511 camera layer.
- * @returns {?object}
- */
-export function floridaCameraToSource(feature) {
-  const a = feature?.attributes;
-  if (!a || typeof a !== 'object') return null;
-  const lat = toFiniteNumber(a.LATITUDE);
-  const lon = toFiniteNumber(a.LONGITUDE);
-  if (!isLikelyFloridaCoordinate(lat, lon)) return null;
-
-  const imageUrl = String(a.IMAGE || '');
-  let image;
-  try {
-    image = new URL(imageUrl);
-  } catch {
-    return null;
-  }
-  // Official image hosts only, HTTPS, no embedded credentials.
-  if (
-    image.protocol !== 'https:' ||
-    !FLORIDA_IMAGE_HOSTS.includes(image.host) ||
-    image.username ||
-    image.password
-  )
-    return null;
-
-  const cameraId = floridaCameraId(imageUrl);
-  if (!cameraId) return null;
-
-  const heading =
-    FLORIDA_DIRECTION_HEADINGS[
-      String(a.DIRECTION || '')
-        .trim()
-        .toUpperCase()
-    ];
-  const hasHeading = Number.isFinite(heading);
-
-  return {
-    id: cameraId,
-    name: String(a.DESCRIPT || '').trim() || `FL511 ${cameraId.slice(3)}`,
-    city: String(a.COUNTY ? `${a.COUNTY} County` : 'Florida'),
-    cityId: 'florida',
-    provider: 'FL511',
-    lat,
-    lon,
-    headingDeg: hasHeading ? heading : fallbackHeadingFromId(cameraId),
-    headingConfidence: hasHeading ? 'high' : 'low',
-    pitchDeg: hasHeading ? -24 : -18,
-    fovDeg: hasHeading ? 56 : 44,
-    rangeM: hasHeading ? 210 : 145,
-    mountHeightM: hasHeading ? 10 : 8,
-    groundElevationM: 5, // Coastal prior; the client's ground snap corrects.
-    feedType: 'image',
-    url: imageUrl,
-    snapshotUrl: imageUrl,
-    sourceKind: 'fl511-open-data',
-    license:
-      'FL511 (FDOT), individual personal use only; other use needs FDOT written consent',
-  };
-}
-
-/**
- * Fetch FL511 (Florida DOT) cameras, keyless: an ArcGIS FeatureServer paged
- * up to 2,000 rows at a time, ordered by the layer's object id so offsets are
- * stable. Paging follows `exceededTransferLimit` and advances by the rows each
- * page returned, so a lower server-side max record count still reads the whole
- * layer. Frames are stills on the Divas Cloud hosts. A redirect on any page
- * drops the pack; any other failed page keeps the rows already read.
- *
- * @returns {Promise<Array<object>>} Normalized camera source objects.
- */
-export async function loadFloridaSourcesFromOpenData() {
-  try {
-    const cameras = [];
-    const seen = new Set();
-    const pageSize = 2000;
-    let offset = 0;
-    // Page ceiling, in case the service ignores resultOffset.
-    for (let page = 0; ; page += 1) {
-      if (page >= FLORIDA_MAX_CATALOG_PAGES) {
-        console.warn(
-          `[CCTV] Florida catalog stopped at the ${FLORIDA_MAX_CATALOG_PAGES}-page ceiling; the catalog may be incomplete`,
-        );
-        break;
-      }
-      // OBJECTID_1 is this layer's object id field (a plain OBJECTID is a 400).
-      const url = `${FLORIDA_CCTV_URL}?where=1%3D1&outFields=*&orderByFields=OBJECTID_1&f=json&resultRecordCount=${pageSize}&resultOffset=${offset}`;
-      let resp;
-      try {
-        resp = await fetch(url, {
-          headers: { Accept: 'application/json' },
-          redirect: 'manual',
-          signal: AbortSignal.timeout(CCTV_SOURCE_FETCH_TIMEOUT_MS),
-        });
-      } catch (error) {
-        console.warn(
-          '[CCTV] Florida catalog page failed:',
-          error?.message || error,
-        );
-        break;
-      }
-      // Release the body on every path that will not read it.
-      const discard = async () => {
-        try {
-          await resp.body?.cancel();
-        } catch {
-          /* no-op */
-        }
-      };
-      if (resp.status >= 300 && resp.status < 400) {
-        console.warn(
-          '[CCTV] Florida catalog redirected; redirects are not followed',
-        );
-        await discard();
-        return [];
-      }
-      if (!resp.ok) {
-        console.warn('[CCTV] Florida camera download failed:', resp.status);
-        await discard();
-        break;
-      }
-      let body;
-      try {
-        body = await readResponseJsonCapped(resp, FLORIDA_MAX_CATALOG_BYTES);
-      } catch (error) {
-        console.warn(
-          '[CCTV] Florida catalog page unreadable:',
-          error?.message || error,
-        );
-        break;
-      }
-      const feats = Array.isArray(body?.features) ? body.features : [];
-      for (const feature of feats) {
-        const camera = floridaCameraToSource(feature);
-        if (!camera || seen.has(camera.id)) continue;
-        seen.add(camera.id);
-        cameras.push(camera);
-      }
-      // ArcGIS sets exceededTransferLimit while more rows remain. A page may
-      // be shorter than pageSize when the layer's max record count is lower.
-      if (body?.exceededTransferLimit !== true || feats.length === 0) break;
-      offset += feats.length;
-    }
-
-    const maxRaw = Number(
-      process.env.CCTV_FLORIDA_MAX_SOURCES || DEFAULT_FLORIDA_MAX_SOURCES,
-    );
-    const maxCount = Number.isFinite(maxRaw)
-      ? Math.max(8, Math.min(4200, Math.floor(maxRaw)))
-      : DEFAULT_FLORIDA_MAX_SOURCES;
-    const prioritized = prioritizeSources(cameras, maxCount, FLORIDA_ANCHORS);
-    console.log(
-      `[CCTV] Loaded Florida camera sources: ${cameras.length} (using nearest ${prioritized.length})`,
-    );
-    return prioritized;
-  } catch (error) {
-    console.warn(
-      '[CCTV] Florida camera download error:',
-      error?.message || error,
-    );
-    return [];
-  }
-}

server/providers/common/request.js

@@ -14,34 +14,16 @@ async function readRequestBodyCapped(req, maxBytes) {
   return Buffer.concat(chunks);
 }
 
-/** Optional cancellation discards buffered data while the request drains. */
+function readRequestBody(req, maxBytes = 1024 * 1024) {
-function readRequestBody(req, maxBytes = 1024 * 1024, signal) {
   return new Promise((resolve, reject) => {
     let total = 0;
     let bodyTooLarge = false;
-    let settled = false;
     const chunks = [];
-    const stopReading = () => {
+    req.on('data', (chunk) => {
-      if (!signal) return;
-      req.off('data', data);
-      req.off('end', end);
-      signal.removeEventListener('abort', abort);
-    };
-    const fail = (error) => {
-      if (signal) {
-        if (settled) return;
-        settled = true;
-        chunks.length = 0;
-        signal.removeEventListener('abort', abort);
-      }
-      reject(error);
-    };
-    const abort = () => fail(signal.reason);
-    const data = (chunk) => {
       // Keep draining after the cap without retaining more bytes. Destroying
       // the request also destroys its socket, so the handler cannot deliver
       // the fixed error response it constructs for BODY_TOO_LARGE.
-      if (bodyTooLarge || settled) return;
+      if (bodyTooLarge) return;
       total += chunk.length;
       if (total > maxBytes) {
         // Same marker readRequestBodyCapped sets, so a caller can tell an
@@ -50,42 +32,15 @@ function readRequestBody(req, maxBytes = 1024 * 1024, signal) {
         chunks.length = 0;
         const error = new Error(`Request body exceeds ${maxBytes} bytes`);
         error.code = 'BODY_TOO_LARGE';
-        fail(error);
+        reject(error);
         return;
       }
       chunks.push(chunk);
-    };
+    });
-    const end = () => {
+    req.on('end', () => {
-      if (settled) {
-        stopReading();
-        return;
-      }
       if (!bodyTooLarge) resolve(Buffer.concat(chunks).toString('utf8'));
-      if (signal) {
+    });
-        settled = true;
+    req.on('error', reject);
-        chunks.length = 0;
-        stopReading();
-      }
-    };
-    const close = () => {
-      fail(
-        new DOMException('Request closed before its body ended', 'AbortError'),
-      );
-      stopReading();
-      req.off('error', fail);
-      req.off('close', close);
-    };
-    if (signal) {
-      // Abort/overflow release retained bytes but keep draining. Retain an
-      // error handler until close, including a late error after end/abort.
-      req.on('close', close);
-      signal.addEventListener('abort', abort, { once: true });
-      if (signal.aborted) abort();
-    }
-    req.on('data', data);
-    req.on('end', end);
-    req.on('error', fail);
-    if (signal && req.destroyed) close();
   });
 }
 

server/providers/common/request.test.mjs

@@ -1,137 +0,0 @@
-import test from 'node:test';
-import assert from 'node:assert/strict';
-import { EventEmitter, getEventListeners } from 'node:events';
-import { readRequestBody } from './request.js';
-
-function fixture() {
-  const req = new EventEmitter();
-  req.pause = () => assert.fail('The reader must keep draining');
-  req.destroy = () =>
-    assert.fail('The reader must preserve the response socket');
-  const owner = new AbortController();
-  return { req, owner };
-}
-
-function finish(req, owner) {
-  assert.doesNotThrow(() => req.emit('error', new Error('late stream error')));
-  req.emit('end');
-  assert.doesNotThrow(() => req.emit('error', new Error('error before close')));
-  req.emit('close');
-  for (const event of ['data', 'end', 'error', 'close'])
-    assert.equal(req.listenerCount(event), 0, event);
-  assert.equal(getEventListeners(owner.signal, 'abort').length, 0);
-}
-
-test('default and cancellable readers preserve byte caps and UTF-8 across chunks', async () => {
-  for (const useSignal of [false, true]) {
-    for (const text of ['', 'hello', 'é']) {
-      const { req, owner } = fixture();
-      const bytes = Buffer.from(text);
-      const body = readRequestBody(
-        req,
-        bytes.length,
-        useSignal ? owner.signal : undefined,
-      );
-      for (const byte of bytes) req.emit('data', Buffer.from([byte]));
-      req.emit('end');
-      assert.equal(await body, text);
-      if (useSignal) finish(req, owner);
-    }
-  }
-});
-
-test('default overflow rejects before end and drains without pausing or destroying', async () => {
-  const { req } = fixture();
-  const rejection = assert.rejects(readRequestBody(req, 2), {
-    code: 'BODY_TOO_LARGE',
-  });
-  req.emit('data', Buffer.from('é'));
-  req.emit('data', Buffer.from('!'));
-  await rejection;
-  req.emit('data', Buffer.alloc(4096));
-  assert.doesNotThrow(() => req.emit('error', new Error('late')));
-  req.emit('end');
-});
-
-test('partial abort settles before end, discards late data and guards errors until close', async () => {
-  const { req, owner } = fixture();
-  const reason = new Error('request deadline');
-  const rejection = assert.rejects(
-    readRequestBody(req, 1024, owner.signal),
-    (error) => error === reason,
-  );
-  req.emit('data', Buffer.from('partial'));
-  owner.abort(reason);
-  await rejection;
-  assert.equal(getEventListeners(owner.signal, 'abort').length, 0);
-  req.emit('data', Buffer.alloc(4096));
-  finish(req, owner);
-});
-
-test('already-aborted and already-closed requests settle and release their listeners', async () => {
-  for (const closed of [false, true]) {
-    const { req, owner } = fixture();
-    if (closed) req.destroyed = true;
-    else owner.abort();
-    await assert.rejects(readRequestBody(req, 1024, owner.signal), {
-      name: 'AbortError',
-    });
-    if (!closed) finish(req, owner);
-    for (const event of ['data', 'end', 'error', 'close'])
-      assert.equal(req.listenerCount(event), 0);
-    assert.equal(getEventListeners(owner.signal, 'abort').length, 0);
-  }
-});
-
-test('overflow keeps its first failure through later abort and stream errors', async () => {
-  const { req, owner } = fixture();
-  const rejection = assert.rejects(readRequestBody(req, 2, owner.signal), {
-    code: 'BODY_TOO_LARGE',
-  });
-  req.emit('data', Buffer.from('é!'));
-  await rejection;
-  owner.abort(new Error('later deadline'));
-  req.emit('data', Buffer.alloc(4096));
-  finish(req, owner);
-});
-
-test('early close and request error reject once; successful end wins over later abort', async () => {
-  for (const event of ['close', 'error', 'end']) {
-    const { req, owner } = fixture();
-    const reason = new Error('request failed');
-    const body = readRequestBody(req, 32, owner.signal);
-    const observed =
-      event === 'end'
-        ? body.then((value) => assert.equal(value, 'ok'))
-        : assert.rejects(
-            body,
-            event === 'close'
-              ? { name: 'AbortError' }
-              : (error) => error === reason,
-          );
-    req.emit('data', Buffer.from('ok'));
-    req.emit(event, reason);
-    owner.abort(new Error('later abort'));
-    await observed;
-    if (event !== 'close') finish(req, owner);
-    assert.equal(getEventListeners(owner.signal, 'abort').length, 0);
-  }
-});
-
-test('a prior data observer can abort synchronously without retaining or resolving that chunk', async () => {
-  const { req, owner } = fixture();
-  const reason = new Error('observer stopped request');
-  const external = () => owner.abort(reason);
-  req.on('data', external);
-  const rejection = assert.rejects(
-    readRequestBody(req, 1024, owner.signal),
-    (error) => error === reason,
-  );
-  req.emit('data', Buffer.from('must be discarded'));
-  await rejection;
-  req.emit('end');
-  req.emit('close');
-  assert.deepEqual(req.listeners('data'), [external]);
-  assert.equal(getEventListeners(owner.signal, 'abort').length, 0);
-  req.off('data', external);
-});

server/providers/common/same-site.js

@@ -41,48 +41,3 @@ export function sameSiteGated(handler) {
     return handler(req, res, next);
   };
 }
-
-/**
- * Proxy header values arrive client-controlled; read one only when it is a
- * single scheme token, never a comma-separated chain.
- * @param {import('node:http').IncomingMessage} req
- * @returns {'http:'|'https:'}
- */
-function forwardedProtocol(req) {
-  if (req.socket?.encrypted) return 'https:';
-  const proto = String(req.headers?.['x-forwarded-proto'] || '')
-    .trim()
-    .toLowerCase();
-  return proto === 'https' ? 'https:' : 'http:';
-}
-
-/**
- * Cross-site gate for keyless routes the map needs in order to render
- * (`/api/terrain/heights`). It refuses the same cross-site browser shapes as
- * `admitSameSite` (a `Sec-Fetch-Site` other than same-origin/none, a foreign
- * or opaque `Origin`) but does not refuse reverse-proxy forwarding headers:
- * those protect credentials and spend, which a keyless route has neither of,
- * and refusing them would break rendering for an instance served behind the
- * reverse proxy the README documents. A single `X-Forwarded-Proto` supplies
- * the scheme an `Origin` is compared against. That header cannot be attached
- * to a cross-site browser request without a CORS preflight this server never
- * answers, and `Sec-Fetch-Site` is still enforced regardless.
- * @param {import('node:http').IncomingMessage} req
- * @param {import('node:http').ServerResponse} res
- * @returns {boolean} True when a 403 was sent.
- */
-export function admitSameSiteKeyless(req, res) {
-  const verdict = admitSameSiteRequest({
-    hostHeader: req.headers?.host,
-    protocol: forwardedProtocol(req),
-    origin: req.headers?.origin,
-    secFetchSite: req.headers?.['sec-fetch-site'],
-    proxyHeaders: {},
-  });
-  if (verdict.ok) return false;
-  res.statusCode = verdict.status;
-  res.setHeader('Content-Type', 'application/json');
-  res.setHeader('Cache-Control', 'no-store');
-  res.end(JSON.stringify({ error: verdict.error }));
-  return true;
-}

server/providers/gemini.js

@@ -1,22 +0,0 @@
-import { createGeminiTokenHandler } from './gemini/realtime.js';
-
-/** Mint constrained Live API credentials; the permanent key stays on Node. */
-function geminiLiveProxy({ annotationGuidance, realtime = {} } = {}) {
-  function install(middlewares) {
-    middlewares.use(
-      '/api/gemini/token',
-      createGeminiTokenHandler({ ...realtime, annotationGuidance }),
-    );
-  }
-  return {
-    name: 'gemini-live-proxy',
-    configureServer(server) {
-      install(server.middlewares);
-    },
-    configurePreviewServer(server) {
-      install(server.middlewares);
-    },
-  };
-}
-
-export { geminiLiveProxy };