Merge branch 'main' into codex/fix-cctv-session-admission

Resolve docs/CURRENT-STATE.md (and scripts/format-scope.json) by keeping both sides.

Co-Authored-By: Claude Opus 5.5 <[email protected]>

.env.example

@@ -83,6 +83,12 @@ 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
@@ -118,8 +124,8 @@ OPENSKY_AUTH_MODE=oauth
 OPENSKY_CLIENT_ID=
 OPENSKY_CLIENT_SECRET=
 
-# Optional: higher Launch Library 2 request allowance. Public access works
-# without a token.
+# Launch Library 2: leave blank for standard public access (no key needed).
+# Optional paid Patreon tokens raise request limits; there is no free API key.
 LL2_API_TOKEN=
 
 # Optional: OpenSky credentials JSON file path (alternative to above)
@@ -201,6 +207,7 @@ 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
@@ -221,6 +228,9 @@ AISSTREAM_API_KEY=
 # CCTV_CALGARY_ROWS_URL=                               # override the Open Calgary catalog URL
 # CCTV_CATALONIA_ENABLED=1                             # set 0 to disable the Servei Català de Trànsit cameras
 # CCTV_CATALONIA_MAX_SOURCES=150                       # cap cameras loaded from Catalonia (~130 exist today)
+# CCTV_HK_ENABLED=1                                   # set 0 to disable the Hong Kong Transport Department cameras
+# CCTV_HK_MAX_SOURCES=1100                            # cap cameras loaded from Hong Kong (~1,013 exist today); min 8, max 1200
+# CCTV_HK_CAMERAS_URL=                                # override the DATA.GOV.HK camera locations XML URL
 # CCTV_KINGCOUNTY_ENABLED=1                            # set 0 to disable the King County (Washington) road cameras
 # CCTV_KINGCOUNTY_MAX_SOURCES=125                      # cap cameras loaded from the King County catalog
 # CCTV_WSDOT_ENABLED=1                                 # set 0 to disable the WSDOT (Washington State) highway cameras
@@ -228,6 +238,7 @@ 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)
@@ -237,6 +248,11 @@ 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_TAIWAN_ENABLED=1                                # set 0 to skip Taiwan Freeway Bureau (MOTC) road cameras
+# CCTV_TAIWAN_MAX_SOURCES=600                          # cap Taiwan freeway cameras (1-2000); no API key required
+# CCTV_TAIWAN_URL=                                     # override the Freeway Bureau MOTC 2.0 CCTV.xml URL
 # 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

.github/workflows/ci.yml

@@ -67,8 +67,6 @@ jobs:
     timeout-minutes: 30
     env:
       GEV_REQUIRE_ALLOCATION_GATE: '0'
-      # Fail on a missed header press unless the panel itself moved.
-      QA_FAIL_ON_RETRY: '1'
     steps:
       - name: Check out source
         uses: actions/checkout@11d5960a326750d5838078e36cf38b85af677262 # v4.4.0
@@ -104,10 +102,6 @@ jobs:
       - name: Street Level gate with Mapillary fixtures
         run: npm run qa:street-level:fixtures -- --strict --url http://localhost:4173
 
-      - name: Portable panel gate
-        if: success() || failure()
-        run: npm run qa:panel-resize -- --url http://localhost:4173
-
       - name: Preview server log
         if: failure()
         run: cat preview.log

.gitignore

@@ -16,6 +16,10 @@ output/
 .gev-cache/
 # Browser QA gate evidence (screenshots, console and network dumps).
 qa-artifacts/
+# Playwright MCP session logs: browser consoles can carry tokens in URLs.
+.playwright-mcp/
+# Local Claude Code settings and preview configs.
+.claude/
 .DS_Store
 .gstack/
 3d-models/

CHANGELOG.md

@@ -317,9 +317,8 @@
   [NotProniss](https://github.com/NotProniss) (#1084).
 
 - Street Level: Panoramax is the fourth provider, keyless. Light its chip
-  (orange; off by default, one provider at a time): from orbit dots show
-  where the federated commons has pictures, and below about 60 km its
-  sequences draw as lines from `api.panoramax.xyz` vector tiles. A click on a
+  (orange; off by default, one provider at a time): below about 60 km the
+  federated commons' sequences draw as lines from `api.panoramax.xyz` vector tiles. A click on a
   line opens that sequence's picture nearest the click without moving the
   camera, flat or 360°, with cones along the sequence around it and ‹ › /
   ← → following the picture's own links. The 360° and since filters apply,
@@ -377,10 +376,10 @@
   Maps JavaScript API) and click a street, or press OPEN STREET VIEW, to
   open Google's own panorama in
   the panel, with its arrows, the address and month in the caption, a link
-  to Google Maps and FOLLOW. Share links carry it in the provider switches
+  to Google Maps. Share links carry it in the provider switches
   (`r.google-1`). One provider is lit at a time (lighting one switches the
   other off), Mapillary by default since it is free. Street View's panoramas
-  are all 360°, so the IMAGERY and SINCE filters and the legend apply to
+  are all 360°, so the IMAGERY and SINCE filters apply to
   Mapillary only and hide while GOOGLE STREET VIEW is lit; its globe marker
   is a Google-blue view cone.
 
@@ -419,21 +418,16 @@
   proposed diagnosis in #927, and [kvnloo](https://github.com/kvnloo) for identifying
   the repair race. Windows/Claude Desktop Cowork confirmation remains outstanding.
 
-- Street Level: a street-level imagery layer modelled on the iD editor's photo
-  overlay, with Mapillary as its first provider (free client token, CC BY-SA 4.0
-  imagery). One right-rail panel holds a chip per provider, shared 360°/flat and
-  captured-since filters, and an embedded viewer with EXPAND, FIT/FILL and
-  FOLLOW (Google 3D only). Coverage lines and image cones are drawn from orbit
-  down to a single street; on Google 3D they sit on the bare earth, refined
-  against the rendered mesh near the camera, so trees and buildings hide them.
-  Share links carry the provider switches, the filters and the panel's collapsed
-  state. A server proxy caches Mapillary coverage tiles (24 h, 1 GiB on disk),
-  refuses cross-site requests, rate-limits per IP and backs off when Mapillary
-  rejects the token or rate-limits.
-
-- The CCTV and Street Level panels are portable: drag the header to float the
-  panel, resize it from any edge or corner, and double-click the header to dock
-  it again. The position persists across reloads.
+- Street Level: street-level imagery from providers, Mapillary first (free
+  client token, CC BY-SA 4.0). A right-rail panel holds a chip per provider,
+  360°/flat and captured-since filters and an embedded viewer with EXPAND and
+  FIT/FILL. Coverage lines (below 60 km) and image cones drape on terrain and
+  Google 3D tiles; opening a photo frames it with one camera flight. Share
+  links carry the provider switches, the filters and the panel's collapsed
+  state. A server proxy adds the token to Mapillary coverage tiles, trims and
+  caches them for 24 h, refuses cross-site requests and redirects, and limits
+  load per IP and upstream. The panel reads KEY REQUIRED without a token and
+  KEY REJECTED when Mapillary refuses it.
 
 - Add Norway's city bikes to the Bike Share layer: Oslo, Bergen and
   Trondheim Bysykkel (Urban Sharing), Kolumbus Bysykkel in Stavanger and

CONTRIBUTING.md

@@ -54,9 +54,8 @@ head -40 scripts/qa-radio.mjs  # what this runnable gate proves and how to run i
 Runnable gate entrypoints document what they assert and how to invoke them.
 Most need a dev server; some also need a specific provider key or port. Follow
 the entrypoint's header rather than assuming every matching file accepts the
-same arguments. Five have an `npm run` alias: `qa:map-source-tray`,
-`qa:panel-resize`, `qa:street-level`, `qa:street-level:fixtures` and
-`qa:transit`.
+same arguments. Four have an `npm run` alias: `qa:map-source-tray`,
+`qa:street-level`, `qa:street-level:fixtures` and `qa:transit`.
 
 If you aren't sure which gate covers your change, search `docs/CURRENT-STATE.md`
 for the feature: it names the gate for many of them, and it's the authoritative
@@ -66,11 +65,10 @@ gate for the feature you changed.
 
 > **CI covers only two of these for you.** The workflow runs the setup policy
 > checks, the formatting and package-boundary checks, the unit suite and the
-> production build, plus a Windows onboarding job, and against the built preview
-> it runs `qa:street-level:fixtures` and `qa:panel-resize`. It does not run
-> `npm run test:track` or any other `qa-*.mjs` gate — those need a live dev
-> server and a browser. Include the applicable local run in your PR's
-> validation evidence.
+> production build, plus a Windows onboarding job. It runs neither
+> `npm run test:track` nor any `qa-*.mjs` gate except the Street Level fixture
+> gate (`street-level-browser` job) — they need a live dev server and a
+> browser. Include the applicable local run in your PR's validation evidence.
 
 ## Share-link layer tokens
 

DATA_SOURCES.md

@@ -20,10 +20,10 @@ How to read this:
 | **NOAA nowCOAST observed weather** (`nowcoast.noaa.gov/geoserver/observations/{weather_radar,satellite}/ows`, WMS 1.1.1) | Rain radar (MRMS base reflectivity, contiguous US, about 4-minute updates) and Satellite clouds (GOES-19/18 Band 14 regional infrared, about 5-minute updates; global infrared mosaic, hourly). Keyless; layer metadata refreshed every 2 minutes, exact-time images cached for up to 24 hours | [NOAA disclaimer](https://oceanservice.noaa.gov/disclaimer.html) | "NOAA nowCOAST · NWS/OAR MRMS radar; NESDIS GOES and global satellite partners" |
 | **NOAA nowCOAST lightning density** (`nowcoast.noaa.gov/geoserver/observations/lightning_detection/ows`) | Lightning density: 15-minute accumulated strike density on an approximately 8 km grid, Americas and Pacific. Keyless; layer metadata refreshed every 10 minutes, exact-time images cached for up to 24 hours | NOAA Level-5 derived product from Vaisala NLDN/GLD360; the [product description](https://ocean.weather.gov/lightning/lightning_pdd.php) permits public distribution of this density product, not of raw Vaisala detections | "NOAA/NWS nowCOAST; derived from Vaisala NLDN/GLD360" |
 | **NOAA NHC / CPHC advisories** (`www.nhc.noaa.gov/CurrentStorms.json` + the `mapservices.weather.noaa.gov` tropical weather summary MapServer) | Cyclone advisories: storm positions, forecast tracks, points and cones for the Atlantic and eastern/central North Pacific. Keyless through `/api/cyclones`; cached for 5 minutes | [NWS public-data terms](https://www.weather.gov/disclaimer); no endorsement implied | "NOAA/NWS NHC / CPHC" |
-| **Mapillary** (vector tiles, Graph API, MapillaryJS) | Street Level: coverage lines, image cones and the embedded viewer. Coverage tiles cached for 24 h | Imagery [CC BY-SA 4.0](https://www.mapillary.com/terms); API under the Mapillary terms with a client token | "© Mapillary contributors, CC BY-SA 4.0", shown on the globe while the provider is on |
+| **Mapillary** (vector tiles, Graph API, MapillaryJS) | Street Level: coverage lines, image cones and the embedded viewer. Coverage tiles kept in server memory for 24 h | Imagery [CC BY-SA 4.0](https://www.mapillary.com/terms); API under the Mapillary terms with a client token | "© Mapillary contributors, CC BY-SA 4.0", shown on the globe while the provider is on |
 | **Google Street View** (Maps JavaScript API) | Street Level, on the Google 3D map only (Google's terms): Google's panorama viewer and nearest-panorama lookups; panorama dates and addresses kept for the session only | Google Maps Platform ToS (your own key + billing; every panorama load is billed) | "Street View imagery © Google" on the globe while the provider is on, and Google's logo and terms in the viewer |
 | **KartaView** (`api.kartaview.org` coverage tiles and photo API, `cdn.kartaview.org` image proxy, `storage*.openstreetcam.org` photos) | Street Level: coverage lines (z13–14 JSON tiles; with the imagery filter on, KartaView's filtered PNG tiles as a mask), nearest-photo lookups, the photo's sequence and the photo itself, fetched by the browser. Keyless; nothing cached beyond the session | Imagery [CC BY-SA 4.0](https://kartaview.org/terms) (KartaView terms §4); the public API needs no token | "© KartaView contributors, CC BY-SA 4.0", shown on the globe while the provider is on |
-| **Panoramax** (`api.panoramax.xyz` meta-catalogue: vector tiles and STAC search; pictures from the federated instance holding each one, e.g. `panoramax.openstreetmap.fr`, `panoramax.ign.fr`) | Street Level: coverage lines and density points, nearest-picture lookups, a sequence's pictures as cones, and the picture itself, fetched by the browser. Keyless; tiles cached by the browser for an hour (the API's own header) | Per picture: mostly [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/), IGN's [Licence Ouverte 2.0](https://www.etalab.gouv.fr/licence-ouverte-open-licence/); the API needs no token | "© Panoramax contributors, licence per picture" on the globe while the provider is on; the caption names each picture's author and licence |
+| **Panoramax** (`api.panoramax.xyz` meta-catalogue: vector tiles and STAC search; pictures from the federated instance holding each one, e.g. `panoramax.openstreetmap.fr`, `panoramax.ign.fr`) | Street Level: coverage lines, nearest-picture lookups, a sequence's pictures as cones, and the picture itself, fetched by the browser. Keyless; tiles cached by the browser for an hour (the API's own header) | Per picture: mostly [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/), IGN's [Licence Ouverte 2.0](https://www.etalab.gouv.fr/licence-ouverte-open-licence/); the API needs no token | "© Panoramax contributors, licence per picture" on the globe while the provider is on; the caption names each picture's author and licence |
 | **OpenStreetMap** | Map and place data (roads, military areas and names, ALPR, place search, outlines); via vector tiles, hourly ALPR extract, bundled data, Nominatim and optional self-configured Overpass | [ODbL 1.0](https://opendatacommons.org/licenses/odbl/1-0/) | © OpenStreetMap contributors |
 | **Google Map Tiles API** (Photorealistic 3D Tiles) + Places/Geocoding | The 3D globe, voice scene context, and on-demand nearby installation search                                                         | Google Maps Platform ToS (proprietary, your own key + billing)                                                                                                                                                                                                                                                                                        | "Google" / "Google Maps" logo — **shown in-app**, required                                                                                  |
 | **OpenSky Network**                                                   | Primary worldwide live-flight snapshot                                                                                              | Non-commercial research/education license                                                                                                                                                                                                                                                                                                             | Schäfer et al., _"Bringing Up OpenSky"_, IPSN 2014 + opensky-network.org                                                                    |
@@ -48,6 +48,7 @@ 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)      |
@@ -62,7 +63,9 @@ How to read this:
 | **Servei Català de Trànsit** (+ Ajuntament de Barcelona, Ajuntament de Terrassa) | CCTV camera catalog + frames, Catalonia                                                                              | [Llicència oberta d'ús d'informació - Catalunya](https://web.gencat.cat/ca/generalitat/dades-indicadors/dades-obertes/llicencies) — attribution REQUIRED                                                                                                                                                                                             | "Servei Català de Trànsit"; partner-supplied cameras also name their owner                                                                  |
 | **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)                                                                  |
+| **Hong Kong Transport Department / DATA.GOV.HK**                      | CCTV camera catalog + frames, Hong Kong traffic snapshot cameras                                                                    | [DATA.GOV.HK Terms of Use](https://data.gov.hk/en/terms-and-conditions) — attribution REQUIRED                                                                                                                                                                                                                                                        | "Hong Kong Transport Department / DATA.GOV.HK"                                                                                              |
 | **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`                                                                                                   |
@@ -110,6 +113,7 @@ The optional Local ADS-B layer and the broadcast-FM receiver use radio you recei
   **Quebec is thinly represented**, and that is upstream rather than a filter here: the province runs its own Info-Smog program, so only a handful of Quebec stations appear in ECCC's national feed. The reporting station count also varies hour to hour as stations report or fall silent.
 
 - **Via Lietuva / Eismoinfo (Lithuania).** Public road-camera catalogs and periodically updated still images from [Eismoinfo](https://eismoinfo.lt/), credited to Via Lietuva / eismoinfo.lt in the app. **Off by default.** The camera endpoints are the eismoinfo.lt website backend and are not among the services listed in Via Lietuva's [open-data statement](https://eismoinfo.lt/eismoinfo-backend/content?id=44), whose conditions are attribution and reuse on the same terms. Until the statement is confirmed to cover the camera photos, the pack loads only when an operator sets `CCTV_LITHUANIA_ENABLED=1`; with the flag unset, empty or any other value, the server makes no request to Eismoinfo. `eismoinfo-backend/camera-info-table` is joined by ID to `layer-static-features/VKR`. Without `lks=true`, the latter returns WGS84 `[latitude, longitude]`; the table's `x/y` instead use LKS-94 metres. Only the official HTTPS `/eismoinfo-backend/image-provider/camera/last?id=…` image endpoint is registered. Catalogs use the shared 15-minute cache; frames are fetched on demand and never bundled or archived. These are periodic snapshots, not continuous video. Camera headings are low-confidence estimates. No API key is required. `CCTV_LITHUANIA_MAX_SOURCES` defaults to 400.
+- **Freeway Bureau, MOTC (Taiwan).** National freeway cameras from the Freeway Bureau's keyless [CCTV static table](https://tisvcloud.freeway.gov.tw/history/motc20/CCTV.xml) in the MOTC 2.0 standard, refreshed daily and fetched at runtime (never bundled). Freeway Bureau traffic data is published under the [Open Government Data License, Taiwan (Version 1.0)](https://data.gov.tw/license), which permits reuse, including commercial reuse, with attribution; the app credits the Freeway Bureau, MOTC, names the dataset and links the licence, as its attribution exhibit asks. The table publishes each camera's MJPEG stream on one of four official camera servers (`cctvn`, `cctvn5`, `cctvc`, `cctvs` under `freeway.gov.tw`). The frame proxy relays single images, so each published stream URL is mapped to the same server's single-JPEG path for the same camera number (`/abs2mjpg/bmjpg` → `/abs2mjpg/jpg`, `/live-view/mjpg/video.cgi` → `/live-view/jpg/image.cgi`); only those exact HTTPS pairs are registered, and the still path is not itself listed in the table. These are on-demand snapshots, not continuous video. Camera headings are low-confidence estimates. No API key is required. The table host does not answer from some networks outside Taiwan (the camera servers do); there the pack is empty, logs one warning and retries hourly. On by default; `CCTV_TAIWAN_ENABLED=0` skips the pack, and `CCTV_TAIWAN_MAX_SOURCES` defaults to 600 (bounded to 1–2000).
 
 - **Google Maps Platform.** You supply your own API key and are bound by [Google's ToS](https://cloud.google.com/maps-platform/terms). Google Maps Content (tiles, geocodes, places) **may not be cached, stored, rehosted, or committed** — this app only ever uses it live, which is the compliant pattern. The "Google" attribution is displayed on the globe and must stay visible. Restrict your key (see [SECURITY.md](SECURITY.md)).
 - **OpenSky Network.** Its license is **non-commercial**, and operational use of the REST API in a live product can require a prior written agreement with OpenSky — even for non-profit/government use. If you deploy this commercially, contact OpenSky for your own terms. The flights layer is a toggle and runs anonymously by default.
@@ -152,7 +156,7 @@ 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 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.
+- **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.
 - **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.
@@ -162,10 +166,13 @@ 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.
+- **Hong Kong Transport Department traffic snapshot cameras.** Keyless. The English camera list is the public DATA.GOV.HK XML at `static.data.gov.hk/td/traffic-snapshot-images/code/Traffic_Camera_Locations_En.xml`; frames are stills on `tdcctv.data.one.gov.hk`, and only that host is registered. Frame URLs are rebuilt from each camera key (`https://tdcctv.data.one.gov.hk/{KEY}.JPG`) rather than taken verbatim from the catalog. Stills were probed to answer directly on that origin with no redirect hop. Frames are fetched at request time and never stored or redistributed. The dataset publishes no camera facing, so headings use the shared id-hash fallback at low confidence and are corrected with the in-app calibration gizmo. By default nearly the full catalog loads (~1,013; pack cap 1,100), prioritized nearest Central, Tsim Sha Tsui, Sha Tin, Tsuen Wan, Tai Po, Fanling, Tuen Mun, Yuen Long and Tseung Kwan O so a lowered cap still spans Hong Kong Island, Kowloon and the New Territories. When the sum of packs exceeds the catalog-wide ceiling, shared round-robin keeps every lane represented. `CCTV_HK_MAX_SOURCES` (8–1200) changes the cap and `CCTV_HK_ENABLED=0` turns the pack off. The DATA.GOV.HK Terms of Use require attribution to the Government / Transport Department / DATA.GOV.HK.
 - **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

@@ -309,6 +309,10 @@ _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.
@@ -377,15 +381,15 @@ 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) · 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                               | 🟢                                                                                                  |
+| 📹 **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) · Hong Kong (Transport Department) · Taiwan (Freeway Bureau, MOTC), 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                               | 🟢                                                                                                  |
 | 📷 **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 |
+| 📷 **Street Level**         | Street-level photos behind one panel, one chip per provider: coverage on the streets, image cones, an embedded viewer with full-screen **EXPAND**. 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            | 🟢                                                                                                  |
 | 🚌 **Transit**              | Live buses, trams, metros, trains and ferries with delayed playback between reports, selected-vehicle trails, and mode-coloured DETECT labels — Boston, Austin, Minneapolis, Helsinki, the Netherlands, Norway, South East Queensland, and nine in Ontario: Toronto (surface vehicles; the subway publishes no positions), Mississauga, Hamilton, Durham Region, York Region, Guelph, Burlington, Barrie and Kingston                                                                                                                                               | Operator GTFS-Realtime feeds            | 🟢                                                                                                  |
 | 🚲 **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 token raises the allowance)                                                         |
+| 🚀 **Space Missions**       | Rolling 30-day launches with payload, stage, and recovery detail                                                                                                                                                                                                                                                                                                                    | Launch Library 2                        | 🟢 (🔴 optional paid 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                           | 🟢                                                                                                  |
@@ -421,9 +425,9 @@ _The Space Missions layer replaying a Falcon 9 ascent — labeled `RECONSTRUCTED
 
 **Setup.** At [mapillary.com/dashboard/developers](https://www.mapillary.com/dashboard/developers), register an application with **Read** access and copy its **Client Token** (`MLY|…`). Paste it into **POWER UP → Mapillary**, or set `MAPILLARY_CLIENT_TOKEN` in `.env` and restart. Without it the panel reads **KEY REQUIRED**. **Google Street View** uses `GOOGLE_MAPS_API_KEY` with the **Maps JavaScript API** enabled for it in Google Cloud; its chip starts off, since every panorama is billed to the key. **KartaView** and **Panoramax** need nothing: their public APIs are keyless.
 
-**Use.** Turn on **Street Level** under DATA LAYERS → Cameras, or with the pill in the STREET LEVEL panel header. Each provider has a chip in its own colour (Mapillary green), and one is lit at a time: lighting one switches the others off. Mapillary, which is free, is lit by default. The **IMAGERY** (ALL / 360° / FLAT) and **SINCE** filters apply to Mapillary, KartaView and Panoramax; Street View panoramas are all 360°, so with Street View lit the filters and legend are hidden. Click a coverage line for its image cones and a cone to open the photo. Light **KARTAVIEW** (purple) and zoom in below about 6 km: its lines are the streets KartaView has photos of, and a click on one opens the photo nearest the click, flat or 360° (drag to look around), with cones along its drive; **‹ ›** or ← → step through the drive (Shift+← →, ↑ ↓ and + − look around a 360° photo; pinch zooms on a phone). Photos KartaView has archived are skipped, and where all are archived the panel says so. For KartaView, **SINCE** goes by upload date, as KartaView's own map does (it can filter by nothing else), and the panel notes it under the slider; KartaView filters its lines on its own server, and a filtered area KartaView has not drawn before can take several seconds, and the unfiltered lines show meanwhile. Light **PANORAMAX** (orange) for the open, federated commons (strongest in France and Belgium): from orbit its dots show where it has pictures, and below about 60 km its lines are sequences. A click on a line opens that sequence's picture nearest the click without moving the camera, flat or 360°, with cones along the sequence around it; **‹ ›** or ← → step through it, and both filters apply. Its caption names the picture's authors (or the instance holding it) and licence (mostly CC BY-SA 4.0; pictures on the IGN instance are Licence Ouverte 2.0). On the **Google 3D** map (Google's terms keep Street View off other maps, where it does not appear), light **GOOGLE STREET VIEW** and click a street from below 3 km, or press **OPEN STREET VIEW** for the view centre, to open Google's panorama there; step along its arrows. Above the photo: **EXPAND**, **FIT / FILL** (Mapillary, and flat KartaView and Panoramax photos), and **FOLLOW** (the globe camera follows the photo's view; Google 3D map only). The caption links to the image on the provider's site, and the globe credits each provider that is on ("© Mapillary contributors, CC BY-SA 4.0", "Street View imagery © Google", "© KartaView contributors, CC BY-SA 4.0", "© Panoramax contributors, licence per picture"). KartaView's own photo pages fail for signed-out visitors, so its link opens the full-size photo.
+**Use.** Turn on **Street Level** under DATA LAYERS → Cameras, or with the pill in the STREET LEVEL panel header. Each provider has a chip in its own colour (Mapillary green), and one is lit at a time: lighting one switches the others off. Mapillary, which is free, is lit by default. Zoom in to street level (below 60 km) for the coverage lines; from orbit the panel says to zoom in. The **IMAGERY** (ALL / 360° / FLAT) and **SINCE** filters apply to Mapillary, KartaView and Panoramax; Street View panoramas are all 360°, so with Street View lit the filters are hidden. Click a coverage line for its image cones and a cone to open the photo. Light **KARTAVIEW** (purple) and zoom in below about 6 km: its lines are the streets KartaView has photos of, and a click on one opens the photo nearest the click, flat or 360° (drag to look around), with cones along its drive; **‹ ›** or ← → step through the drive (Shift+← →, ↑ ↓ and + − look around a 360° photo; pinch zooms on a phone). Photos KartaView has archived are skipped, and where all are archived the panel says so. For KartaView, **SINCE** goes by upload date, as KartaView's own map does (it can filter by nothing else), and the panel notes it beside the SINCE value (ANY DATE (by upload date)); KartaView filters its lines on its own server, and a filtered area KartaView has not drawn before can take several seconds. Light **PANORAMAX** (orange) for the open, federated commons (strongest in France and Belgium): below about 60 km its lines are sequences. A click on a line opens that sequence's picture nearest the click without moving the camera, flat or 360°, with cones along the sequence around it; **‹ ›** or ← → step through it, and both filters apply. Its caption names the picture's authors (or the instance holding it) and licence (mostly CC BY-SA 4.0; pictures on the IGN instance are Licence Ouverte 2.0). On the **Google 3D** map (Google's terms keep Street View off other maps, where it does not appear), light **GOOGLE STREET VIEW** and click a street from below 3 km, or press **OPEN STREET VIEW** for the view centre, to open Google's panorama there; step along its arrows. Above the photo: **EXPAND** (full screen; Esc leaves) and **FIT / FILL** (Mapillary, and flat KartaView and Panoramax photos). The caption links to the image on the provider's site, and the globe credits each provider that is on ("© Mapillary contributors, CC BY-SA 4.0", "Street View imagery © Google", "© KartaView contributors, CC BY-SA 4.0", "© Panoramax contributors, licence per picture"). KartaView's own photo pages fail for signed-out visitors, so its link opens the full-size photo.
 
-Drag the panel header to float the panel, and resize it from any edge. Double-click the header or collapse it to put it back in the rail. Share links carry the provider switches and filters (`0.m.0` Mapillary off, `0.m.0_0.r.google-1` Street View on, `0.m.0_0.r.google-0*kartaview-1*panoramax-0` KartaView on and `0.m.0_0.r.google-0*kartaview-0*panoramax-1` Panoramax on, as the app writes them (`0.m.0_0.r.kartaview-1` and `0.m.0_0.r.panoramax-1` work too; a link that leaves out `m` keeps Mapillary, the default, lit), `0.p.p` panoramas only, `0.s.365` the last year). To add a provider, implement the contract in `src/layers/streetLevel/registry.js` and register it in `src/app/layers/streetLevel.js`.
+Share links carry the provider switches and filters (`0.m.0` Mapillary off, `0.m.0_0.r.google-1` Street View on, `0.m.0_0.r.google-0*kartaview-1*panoramax-0` KartaView on and `0.m.0_0.r.google-0*kartaview-0*panoramax-1` Panoramax on, as the app writes them (`0.m.0_0.r.kartaview-1` and `0.m.0_0.r.panoramax-1` work too; a link that leaves out `m` keeps Mapillary, the default, lit), `0.p.p` panoramas only, `0.s.365` the last year). To add a provider, implement the contract in `src/layers/streetLevel/registry.js` and register it in `src/app/layers/streetLevel.js`.
 
 ## 🎖️ Field Missions
 
@@ -527,9 +531,11 @@ _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** | 🚀 Higher space-missions request allowance (🟢 works without) | [thespacedevs.com](https://thespacedevs.com)       |
+| 🔴  | **Launch Library 2** | 🚀 Optional paid token for higher limits (🟢 no key needed for public access) | [thespacedevs.com/supportus](https://thespacedevs.com/supportus) |
 
 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

@@ -29,7 +29,7 @@ These are designed to be used directly in the browser (like a Mapbox public toke
 
 1. **Google Maps API key** — loads Photorealistic 3D Tiles directly and powers Street View (Maps JavaScript API; add it to the key's API restrictions). **Restrict it** (HTTP referrer + API restriction to the required Google APIs) in the Google Cloud Console. An unrestricted key in a public deployment can be abused and billed to you. Restrict it to the **Map Tiles API and Maps JavaScript API only**: a referrer restriction applies to the Maps JavaScript API and the client SDKs, not to the web services, so a key carrying Geocoding under one is refused with `API keys with referer restrictions cannot be used with this API`. Search does not need it — geocoding goes through the server proxies above (#363).
 2. **Cesium ion token** (`CESIUM_ION_TOKEN`, optional — for ion-hosted Google Photorealistic 3D Tiles, Bing world imagery, and world terrain) — used as `Cesium.Ion.defaultAccessToken` client-side. Use a public **`assets:read`** token with **URL restrictions** for any hosted deployment. The Community plan has eligibility and usage limits; a public token is not a secret, but it can still consume the account's quota.
-3. **Mapillary client token** (`MAPILLARY_CLIENT_TOKEN`, optional, Street Level) — used by the MapillaryJS viewer and Graph API lookups in the browser, and by the server's coverage-tile proxy. Mapillary client tokens are meant for browser use.
+3. **Mapillary client token** (`MAPILLARY_CLIENT_TOKEN`, optional, Street Level) — used by the MapillaryJS viewer and Graph API lookups in the browser, and by the server's coverage-tile proxy, which sends it only to `tiles.mapillary.com` over HTTPS (an upstream redirect is refused and answered 502, never followed) and caches tiles in memory only. Mapillary client tokens are meant for browser use.
 
 > The explicit browser `define` block in `build/vite.js` controls exactly what reaches the client: only these three keys. Everything else stays server-side.
 
@@ -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.
+- **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.
 - **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

@@ -0,0 +1,12 @@
+- `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/1197-launch-library-provider-guidance.md

@@ -0,0 +1,5 @@
+- 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

@@ -0,0 +1,3 @@
+- 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

@@ -0,0 +1,5 @@
+- 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

@@ -0,0 +1,4 @@
+- 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/1205-cctv-tool-routing.md

@@ -0,0 +1,3 @@
+- Report actual outcomes when voice enables or disables CCTV through the shared
+  layer lifecycle, including failed and cancelled changes (manjunath22466,
+  #1205).

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

@@ -0,0 +1,3 @@
+- 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

@@ -0,0 +1,4 @@
+- 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).

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

@@ -0,0 +1,4 @@
+- Harden the Tarktee (Estonia) DATEX2 camera catalog fetches: refuse redirects,
+  cancel both response streams when either response fails or overflows the 4 MB
+  byte cap, and deduplicate camera IDs before per-pack prioritization
+  (yaka0007, #1233).

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

@@ -0,0 +1,5 @@
+- 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/1235-location-resolution.md

@@ -0,0 +1,3 @@
+- Require a geocoded containment anchor for ambiguous analyst region names,
+  preserve boundary provenance and cancellation safety, and retain exact-name
+  precedence for natural outlines (manjunath22466, #1235).

changelog.d/1237-taiwan-freeway-cctv.md

@@ -0,0 +1,4 @@
+- Add Taiwan's national freeway cameras from the Freeway Bureau, MOTC to CCTV:
+  ~1,800 cameras read at runtime from the official MOTC 2.0 open-data table,
+  with on-demand snapshots and attribution. No API key is required; set
+  `CCTV_TAIWAN_ENABLED=0` to skip it (419vive, #1237).

changelog.d/1267-cctv-session-admission.md

@@ -0,0 +1,3 @@
+- Gate CCTV HLS media requests before session work, bind leases to the direct
+  peer, and bound per-peer leases across shared sessions (asturksever, #1267).
+- Keep headful CCTV QA rendering active when its window is occluded (asturksever, #1267).

changelog.d/1283-satellite-cache-provenance.md

@@ -0,0 +1,3 @@
+- Report cached CelesTrak satellite records as stale in the Data Layers row,
+  preserving separate core and dense catalog provenance through refresh,
+  removal and lifecycle cleanup (rudycelekli, #1283).

changelog.d/1284-route-plausibility-segment.md

@@ -0,0 +1,3 @@
+- Keep aircraft route labels on the scheduled airport leg instead of accepting
+  its distant great-circle extensions, preserving generous endpoint tolerance
+  across the signed-angle branch cut (rudycelekli, #1284).

changelog.d/1286-since-note-inline.md

@@ -0,0 +1,4 @@
+- The Street Level SINCE note sits on the value's line, in its type and a
+  size smaller: with KartaView lit it reads ANY DATE (by upload date). It
+  had lost its size variable in the Street Level slim-down and rendered
+  larger than the value, on a line of its own (asturksever, #1286).

changelog.d/1287-shared-sliders.md

@@ -0,0 +1,3 @@
+- Give ordinary sliders a shared native control and consistent track, thumb,
+  value, focus and disabled styling while preserving feature behavior and
+  specialized controls (mazy1998, #1287).

changelog.d/1301-shared-segmented-selectors.md

@@ -0,0 +1,5 @@
+- Unify segmented selectors for model coverage, detection allocation, drawing
+  shape, Street View and imagery comparison while preserving their existing
+  behavior. Keep compact labels such as FILL and FLAT on one line, and let
+  collapsed Weather release space to the open rail panel. Reserve the full mode
+  button height in Recent Imagery so keyboard focus is not clipped (mazy1998, #1301).

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

@@ -0,0 +1,9 @@
+- 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

@@ -0,0 +1,9 @@
+- 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

@@ -0,0 +1,7 @@
+- 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

@@ -0,0 +1,4 @@
+- 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

@@ -0,0 +1,6 @@
+- 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

@@ -0,0 +1,17 @@
+- 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/974-street-level-slim.md

@@ -0,0 +1,6 @@
+- Street Level is rebuilt around one small provider registry: Mapillary,
+  KartaView, Panoramax and Google Street View share one coverage drawer and
+  one photo viewer, one source lit at a time. Floating and docked panels,
+  FOLLOW, surface modes, the legend and the Mapillary proxy's disk cache are
+  gone; `.gev-cache/mapillary/` from earlier runs is no longer read and can be
+  deleted (gekh, #974).

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

@@ -0,0 +1,8 @@
+- 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).

changelog.d/990-hong-kong-cctv.md

@@ -0,0 +1,7 @@
+- Add Hong Kong Transport Department traffic snapshot cameras as a keyless CCTV
+  source pack: the public DATA.GOV.HK English locations XML, frames pinned to
+  `tdcctv.data.one.gov.hk`, with DATA.GOV.HK Terms of Use attribution. By
+  default nearly the full TD catalog (~1,013 cameras; cap 1,100) loads,
+  prioritized across Hong Kong Island, Kowloon and the New Territories. Headings
+  use the shared id-hash fallback at low confidence. `CCTV_HK_MAX_SOURCES` sets
+  the cap (8–1,200) and `CCTV_HK_ENABLED=0` turns the pack off (JCY2515, #990).

docs/CODE-BOUNDARIES.md

@@ -356,8 +356,8 @@ drag or final change. Feature adapters own data mapping and service subscription
 generic modules own DOM/listeners/timers and release them in `destroy()`.
 
 Keep persistence with panel chrome: collapse uses
-`godsEyeView.v6.panelCollapsed.<panelId>`, position uses
-`godsEyeView.v8.panelPos.<panelId>`, and share state uses the registered panel id.
+`godsEyeView.v6.panelCollapsed.<panelId>`, positions are
+not stored (`godsEyeView.v8.panelPos.<panelId>` stays reserved), and share state uses the registered panel id.
 Do not rename existing
 ids or reset persistence versions when adding a body. The WEATHER adapter is
 `src/ui/weatherPanel.js`; its observed-history selection remains transient.

docs/CURRENT-STATE.md

@@ -1,5 +1,21 @@
 # God's Eye View Current State
 
+Analyst region queries resolve unique Natural Earth names offline without
+geocoding, so Gold Coast and Ivory Coast name the West African natural regions.
+Duplicate names require a geocoded containment anchor; when several entries for
+the same name contain that anchor, the lookup stays unresolved rather than
+selecting the largest entry. Natural outlines try exact names before aliases and
+broader suffix variants. Follow-ups retain boundary provenance, and cancelled
+lookups preserve the previous analyst cohort and boundary source. Navigation
+search keeps a successful geocode, with no search or view-based region recovery.
+
+CCTV live-media requests are same-site gated before catalog or media work, including
+HLS renewal, segment reads and DELETE cleanup. HLS leases belong to their socket
+peer (IPv4-mapped IPv6 is normalized), with eight leases per peer across the two
+global sessions. Peers behind the same NAT share that budget; this is resource
+admission, not authentication. Native same-origin video and range requests remain
+supported.
+
 Shared distance checks use `src/geoDistance.js` with `{ lat, lon }` points and
 the IUGG mean spherical Earth radius, 6371.0088 km. `greatCircleKm` is
 canonical; `greatCircleMeters` is its exact metre conversion. Missing,
@@ -112,7 +128,14 @@ 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. Voice offers the same queries next to its app
+lists at 25 rows by default. `aircraft_in_area` and `vessels_in_area` can also
+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
@@ -489,6 +512,11 @@ 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
@@ -606,10 +634,20 @@ 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. 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. 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.
+
+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.
 
+`createGevActionRunner` routes `control_cctv` enable/disable through the shared
+layer visibility lifecycle. Results distinguish successful changes from
+manager-reported failures or cancellation and report enabled state and lifecycle
+uncertainty. A caller-supplied abort signal reaches the manager; a late abort
+preserves an already committed change. Missing-layer errors and other CCTV
+actions retain their existing behavior. The exported `controlCctv` helper refuses direct
+enable/disable requests and directs callers to `set_layer_visibility`.
+
 `src/voice/layerManifest.js` declares each catalog layer's voice capabilities: spoken aliases, `toggle`, in-view `context`, `track`, and analyst `query` fields with type and unit, or `noQuery` with the reason. The `set_layer_visibility`, `show_data_layers_menu`, `get_entity_context` and `analyst_query` layer enums, the runner's alias table and the analyst field hints are generated from it. `src/voice/layerManifest.test.mjs` fails when a catalog layer is neither listed nor named in `VOICE_OFF_LAYERS` (today only the two scene-driven Bhote Koshi layers). Global Context is listed with `toggle: false`; `set_context_mode` reaches it. `set_panel_open` also opens `weather-panel` and `recent-imagery-panel`.
 
 Portable source exports provide Radio Browser station normalization, CCTV feed types and regional records independently of HTTP middleware. Radio normalization accepts an explicit URL policy; the standalone directory retains its existing HTTPS rules. Tile coordinate validation accepts explicit zoom bounds with unchanged traffic defaults. Cache, request and rendering owners remain unchanged.
@@ -637,7 +675,7 @@ The UI facade composes separate owners for navigation authority, share restorati
 visual settings and panel chrome. Navigation owns request generations and follow
 handoff; restoration owns its coordinator, deferred notices, gestures and timer;
 visual settings own style/detection overrides and sensor cleanup; panel chrome
-owns disclosure, docking and Cockpit panel snapshots. Each takes explicit
+owns disclosure and Cockpit panel snapshots. Each takes explicit
 operations and reads instead of the complete shell. Existing controls, share
 formats and one-application-per-page behavior are preserved.
 
@@ -803,7 +841,11 @@ Viewport limits, saturation retry, placement, query caps and controls are retain
 
 Satellite and mission layers expose separate factories through `./layers/satellites`
 and `./layers/launches`. Each owns its catalog, render state, tracking, interaction
-and teardown. Source adapters retain the existing CelesTrak and Launch Library
+and teardown. Satellite core and dense catalogs retain upstream stale-cache
+provenance only for admitted records; duplicate or invalid entries cannot taint
+a fresh winning record. Dense removal clears only its own provenance, and a
+fresh core rebuild or lifecycle reset replaces the corresponding ownership.
+Source adapters retain the existing CelesTrak and Launch Library
 endpoints; standalone entries provide scene services and the satellite dependency.
 The mission factory separates paths, replay, camera, panel, overlays and placement.
 Launch Library pad coordinates retain unknown values: missing fields use the
@@ -812,7 +854,11 @@ 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. Catalog groups, propagation cadence,
+snapshots preserve the last accepted display. A Launch Library stale-cache fallback
+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
@@ -959,10 +1005,9 @@ start with current state, isolate listener failures and stop on disposal.
 
 The standalone entry composes the UI with the application's existing layer,
 terrain, navigation and rendering operations. The shell receives those instances
-and assembles the controls. Panel layout scheduling, position preferences and
-active drags, loading notices, recording presentation and DOM lookup have focused
+and assembles the controls. Panel layout scheduling, loading notices, recording presentation and DOM lookup have focused
 owners. Disposal revokes queued presentation and listeners before asynchronous
-Context restoration, cancels an unfinished drag without saving it, restores the
+Context restoration, restores the
 recording HUD and releases status decoration without replacing accessible text.
 The ordinary control snapshot includes the current 3D model toggle and mode.
 
@@ -1075,6 +1120,26 @@ The images are periodically updated road-condition photographs, not continuous
 video; camera poses use the existing low-confidence heading prior.
 `CCTV_LITHUANIA_MAX_SOURCES` sets its cap (default 400, bounded to 1–1000).
 
+## Taiwan CCTV source pack
+
+The CCTV catalog includes Taiwan national freeway cameras from the Freeway
+Bureau, MOTC. One keyless request reads the daily MOTC 2.0 `CCTV.xml` table
+(~1,800 cameras); the request refuses redirects, has a 15-second deadline and a
+6 MiB response cap, and uses the shared 15-minute cache and fair catalog
+allocation. A failed download serves the last good table (up to a day old),
+or an empty pack, and is not retried for an hour: the catalog host does not
+answer from some networks outside Taiwan, and without the backoff every refresh
+there would wait out the connect timeout. The table
+publishes MJPEG stream URLs; each is mapped to the same camera server's
+single-JPEG path for the same camera number, and only those exact HTTPS pairs
+on the four `freeway.gov.tw` camera servers are registered with the frame
+proxy. Camera keys come from the server and camera number, because published
+CCTV IDs contain Chinese place names and a few repeat across cameras. Poses use
+the low-confidence heading prior. `CCTV_TAIWAN_ENABLED=0` disables the pack;
+`CCTV_TAIWAN_MAX_SOURCES` sets its cap (default 600, bounded to 1–2000), and
+`CCTV_TAIWAN_URL` overrides the table URL.
+Gate: `src/data/cctvTaiwan.test.mjs`.
+
 ## DriveBC CCTV source pack
 
 The CCTV catalog adds DriveBC highway cameras for British Columbia alongside the
@@ -1166,6 +1231,32 @@ The application supplies actions and retains effect settings, restore claims and
 rendering. Native keyboard editing, model modes and current defaults are preserved.
 Destroying the UI removes these listeners before asynchronous teardown.
 
+Ordinary sliders share the native range component in `ui/slider.js` and the
+`gev-quantitative-slider` surface in `ui/styles/slider.css`. Display, shader
+parameters, volume, replay speed, weather settings/history, imagery opacity and
+Street View's date filter use the same rail, thumb, value styling, keyboard focus and disabled state.
+Generated controls use `createSlider`; static templates apply the same class.
+Feature owners retain bounds, steps, formatted values, input/change timing and
+listener cleanup. The radio tuning dial, imagery comparison divider and event
+comparison/progression controls keep their specialized presentation and behavior.
+
+## Segmented selectors
+
+Segmented selectors use the controlled DOM adapter in `ui/segmentedControl.js`
+and the shared `gev-segmented` / `gev-segment` surface. Model coverage, label
+allocation, drawing shape, Street View fit/panorama filters and imagery mode keep
+their feature-owned values, actions and persistence. Painting a restored value
+does not emit a change or move focus. Existing keyboard policies remain explicit:
+Street View uses arrows/Home/End with one tab stop, imagery mode uses arrows from
+its controlled selection, and Display keeps its existing native button behavior.
+Pure value navigation is separate from DOM rendering for reuse by a future view.
+Segments keep their word minimum width: compact inline groups such as FIT/FILL
+and ALL/360°/FLAT must not break short labels mid-word. Collapsed Weather follows
+the same exclusive-rail hiding rule as the other readouts.
+The imagery mode row reserves 26px for the 24px buttons and group borders so
+the complete button and inset keyboard-focus outline remain visible.
+Browser acceptance: `QA_BASE_URL=http://127.0.0.1:4173 node scripts/qa-segmented-controls.mjs`.
+
 ## Application shortcuts and shader parameter controls
 
 `ui/input` supplies the bubbling application shortcut listener and generated
@@ -1192,6 +1283,10 @@ 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.
@@ -1441,6 +1536,18 @@ 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.
@@ -1478,6 +1585,14 @@ 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
@@ -2664,6 +2779,17 @@ 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
@@ -2933,6 +3059,13 @@ down | auth-failed` (plus the unchanged `missing-key`/`unsupported`) with
 >   position getter reads only `_trackedDisplayCached`, the same authoritative
 >   Cartesian already consumed by the tracked visual and camera, and never
 >   advances dead reckoning from the host frame.
+> - **Scheduled route plausibility:** Aircraft route labels and selected-route
+>   context reject the distant backwards, forwards and antipodal extensions of
+>   an airport pair's great circle. The existing 130 km endpoint admission and
+>   200 km cross-track tolerance remain; a projected fix outside the finite
+>   origin-to-destination minor arc also has a generous 200 km extension at
+>   either end. Missing coordinates and coincident or antipodal endpoint pairs
+>   retain their loose, unjudgeable behavior; vertical-trend checks are unchanged.
 > - **Aircraft label convention (both flight layers, 2026-08-18):** every civil
 >   and military label surface resolves **callsign → registration → icao24**
 >   (`_contactLabel()` in `flights.js`; the same chain inline in
@@ -3395,7 +3528,7 @@ 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) + 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)                                                                      |
+| 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) + Hong Kong Transport Department + FL511 (FL, opt-in) + Freeway Bureau, MOTC (Taiwan) + 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                                                                               |
@@ -3404,7 +3537,7 @@ its criteria cannot be silently ignored.
 | Dams ▰                 | OpenInfraMap/OSM extract (bundled)                                                                                                                                                              | `src/data/localLayers.js`                             | —                                                        | static                                                                            |
 | Submarine Cables ◠     | TeleGeography public map (bundled)                                                                                                                                                              | `src/data/telegeographySubmarineCables.js`            | —                                                        | static                                                                            |
 | FIRMS Active Fires ▲   | NASA FIRMS live (VIIRS ×3 NRT + MODIS NRT, trailing 24h)                                                                                                                                        | `src/data/firmsHeatmap.js`                            | `/api/firms` (`FIRMS_MAP_KEY`)                           | 10 min (proxy TTL 30 min)                                                         |
-| Street Level 📷 | Street-level imagery; Mapillary is the first provider (vector tiles, Graph API, MapillaryJS) | `src/layers/streetLevel/` via `src/app/layers/streetLevel.js` | `/api/mapillary/status`, `/api/mapillary/tiles/coverage/{z}/{x}/{y}` (`MAPILLARY_CLIENT_TOKEN`) | camera-driven (320 ms debounce, ≤9 tiles, cached 24 h) |
+| Street Level 📷 | Mapillary street-level imagery (vector tiles, Graph API, MapillaryJS) | `src/layers/streetLevel/` via `src/app/layers/streetLevel.js` | `/api/mapillary/status`, `/api/mapillary/tiles/coverage/{z}/{x}/{y}` (`MAPILLARY_CLIENT_TOKEN`) | camera-driven (320 ms debounce, ≤9 tiles, server memory cache 24 h) |
 | Wind 🌬                 | NOAA GFS 10 m wind (keyless, 0.25°→1° grid; animated particles)                                                                                                                                 | `src/data/wind.js`                                    | `/api/wind`                                              | 1 h (forecast cycle)                                                              |
 | GNSS Integrity 📡 (`gnss-integrity`) | adsb.lol point snapshot, low navigation accuracy binned per 0.5° cell (GEV NIC/NACp threshold + gpsjam.org formula and bands, keyless, ODbL) | `src/layers/gnss/` via `src/app/layers/gnss.js` | `/api/gnss-integrity` | camera-driven (600 ms debounce, minimum 2.5 s between reads) + 60s poll (server cache 60 s; 30 min rolling window) |
 | Fire Perimeters 🔥 | NIFC WFIGS current interagency perimeters (keyless, paged past the 2000-record cap); InciWeb catalog + incident page origin and update time checks for verified incident-page links | `src/layers/perimeters/` via `src/app/layers/perimeters.js` | `/api/fire-perimeters` + `/api/fire-perimeters/inciweb/*` | 5 min (server caches: catalog 1 h; publication 30 min) |
@@ -3436,8 +3569,8 @@ by `scripts/qa-emergency-squawk.mjs`. Both accept `--timeout-ms` for slow boot.
 
 Fire Perimeters uses capped, timed server reads with stale-on-error caching and a per-client limit. Unchanged snapshots retain geometry; link checks cancel on disable or selection change, and the row legend shows reported containment.
 
-Street Level is a collapsible right-rail panel (`#street-level-panel`, layer
-token `0`, option owner `street-level`, panel `ui` token `t`) that starts
+Street Level is a docked, collapsible right-rail panel (`#street-level-panel`,
+layer token `0`, option owner `street-level`, panel `ui` token `t`) that starts
 collapsed. It opens itself only when the user, voice or a tool switches the
 layer on or a photo opens, never on a restore, and those opens are not stored.
 Like the iD editor's photo overlay, it has one chip per registered provider,
@@ -3449,31 +3582,30 @@ sequence is GEV cyan. Share options: `m` (Mapillary), `r` (the other providers'
 e.g. `google-1` for Street View), `p` (`a`/`p`/`f` panoramas), `s` (since, days). Mapillary, Google
 Street View, KartaView and Panoramax are registered. Without
 `MAPILLARY_CLIENT_TOKEN` the panel reads KEY REQUIRED and the controls are
-disabled. With it, coverage draws as z0–5 overview points from orbit and z11–14
-sequence lines below 60 km; the proxy strips the unused `image` layer from z14
+disabled. With it, coverage draws as z11–14 sequence lines below 60 km; the proxy strips the unused `image` layer from z14
 tiles (12 MB → ~80 KB) and shares one upstream fetch between concurrent
 requests for a tile.
 
-Mapillary coverage ranks unique tile addresses before applying the 16-tile
-overview budget. Overlapping dateline halves in a polar view therefore do not
-waste overview slots on the same tile; loading already skips duplicate keys.
+Coverage is z11–14 sequence lines below 60 km; above that nothing is drawn and
+the panel says to zoom in. Tiles come from the visible ground within range of
+the camera, nearest first, at most 9 (the halves of a view across
+the date line count a shared tile once). Lines are draped
+`GroundPolylinePrimitive`s (`ClassificationType.BOTH`), so they follow terrain
+and Google 3D tiles alike; cones and the photo marker are ground-clamped
+billboards with a horizon cull. Without `MAPILLARY_CLIENT_TOKEN` the panel
+reads KEY REQUIRED, says which key to add and disables the filters; a rejected
+key reads KEY REJECTED and stops tile requests until the layer goes off; a 429
+pauses them for its Retry-After.
 
-On Google 3D (`photoreal`) at street zoom (in below 1,400 m above ground, out
-above 1,800 m) the surface mode switches from `draped` to `terrain`: draped
-lines land on roofs and tree tops, so `groundCast.js` instead places lines,
-cones and the marker 2 m above the bare earth from `/api/terrain/heights`, and
-the mesh hides what is behind buildings and trees. A tile is drawn draped until
-its heights arrive; a geoid fallback leaves it draped. Within 900 m of the
-camera, `meshSampler.js` samples the rendered surface (`scene.sampleHeight`,
-~11 m cells, nearest first, 6 ms idle budget) so lines also follow trenches,
-steep streets and roads under trees. It uses the mesh floor's rules (the
-visible tileset has finished streaming, a real bare-earth prior, the shared
-mesh window) and probes a cell again once the camera is half as far from it,
-down to 40 m, so coarse early samples are replaced as finer tiles load. A
-failed probe keeps the last good sample and distance and is retried after the
-miss cooldown. Roads on elevated decks are still drawn at
-ground level. Framing a photo ignores mesh samples far below the bare earth
-(unloaded tiles).
+The server proxy (`server/providers/mapillary.js`) adds the token to
+coverage-tile requests (the browser holds it too, for MapillaryJS and the Graph
+API), serves only z11–14 coverage, refuses upstream redirects, strips the
+unused `image` layer, shares one fetch per tile, runs at most six at once
+(cancelling those every client has left) and keeps tiles in memory for 24 h
+(a body too big to be a trimmed tile is served but not kept). While Mapillary
+rate-limits, the proxy answers 429 itself until the Retry-After (seconds or an
+HTTP date, at most 10 minutes) is over, so the rest of a view does not go on
+asking.
 
 The header pill is the layer switch. Lighting a chip swaps the source;
 clicking the lit chip turns the layer off. A chip without a usable key
@@ -3484,19 +3616,18 @@ their keys but a switched-off one would draw with a key already set (no
 Mapillary token, Street View on Google 3D with a Google key), the layer
 reports it (`keyAlternatives`), and the panel's KEY REQUIRED, its coverage
 line and the layer row's tooltip say to light it. The
-viewer sits under the header with EXPAND, FIT/FILL, FOLLOW and close above the
-image. FOLLOW needs the Google 3D map stack (`attachMapStackController`) and
-stops when the stack changes. Camera moves go through the application's
-navigation (`attachNavigation`), which releases aircraft and satellite tracking
-and is refused in the cockpit: turning FOLLOW on claims the camera at once, and
-FOLLOW stops when another feature takes it; a photo takes a deferred ticket
-when it starts opening and frames only if nothing newer took the camera while
-it loaded. SINCE is a stepped slider whose readout names the
-cut-off date. The panel is portable (`street-level-panel` spec, minimum
-320 × 280, `dockOnCollapse`): a floating window gives spare height to the
-viewer, and collapsing it, double-clicking the header or SHRINK after EXPAND
-docks it. At phone width (≤720 px) the viewer height is derived from the rail
-band so the whole photo fits.
+viewer sits under the header with EXPAND, FIT/FILL and close above the
+image. SINCE is a stepped slider whose readout names the cut-off date.
+
+MapillaryJS loads on the first photo. Opening one frames it with a single
+camera flight through the application's deferred navigation (`begin` /
+`reassert`): it releases tracking, is refused in the cockpit, and is skipped
+if newer navigation took the camera while the photo loaded; closing the photo
+cancels it. EXPAND is the browser's Fullscreen API on the viewer element; on
+iPhone, which has no element fullscreen, the viewer opens as a top-layer
+popover instead (hidden where neither API exists). Clean View, recording and
+the cockpit take an expanded photo out of full screen. At phone width the
+viewer height comes from the rail band so the whole photo fits.
 
 Providers implement the contract in `src/layers/streetLevel/registry.js`. The
 core routes clicks by pick prefix, swaps viewer adapters in the one host,
@@ -3505,9 +3636,10 @@ add a provider: implement the definition, register it in
 `src/app/layers/streetLevel.js` and add its modules to
 `scripts/package-boundaries.json`; its share switch travels in `r` by id.
 A provider with line coverage builds it on `lineCoverage.js` (camera-driven
-XYZ tiles, draped or cast to bare earth, selection recolouring) and its cones
+XYZ tiles near the ground, draped, the selected sequence drawn again over
+them) and its cones
 on `sequenceCones.js`, passing its tile fetch, zoom ladder, colours and pick
-prefixes; Mapillary's `coverage.js` and `sequences.js` are such wrappers. With providers on different keys the
+prefixes; Mapillary, KartaView and Panoramax all do. With providers on different keys the
 layer's `requiresKeyId` is null and each chip reports its own key.
 
 Google Street View (`providers/google/`) runs on the Maps JavaScript API with
@@ -3516,7 +3648,7 @@ on first use (`mapsLoader.js`, CSP `script-src https://maps.googleapis.com`).
 Its chip starts off (`defaultOn: false`; a link without its switch keeps it off) because every
 panorama load is billed to the key. Google's terms forbid Street View beside
 non-Google maps, so the provider declares `requiresMapStack: 'photoreal'`:
-off Google 3D it does not appear at all (no chip, legend swatch, globe
+off Google 3D it does not appear at all (no chip, globe
 credit, layer source or button, and Google's script is not loaded), lookups
 and opens skip it, and leaving Google 3D closes its panorama; the share
 option keeps the user's choice for when Google 3D returns. Google offers no coverage layer
@@ -3538,9 +3670,8 @@ marker is a Google-blue view cone (`marker: {kind: 'view-cone'}`) in place
 of GEV's amber pin. Its
 panoramas are all 360° and it draws no coverage, so it declares `filters: []`
 (a provider's `filters` default to both `pano` and `since`): lookups ignore
-the IMAGERY and SINCE filters, the panel hides each filter row no lit provider
-honours (`filterControls`), and the legend lists only providers that draw
-lines, with "Selected" only beside one of them. The viewer is Google's `StreetViewPanorama` in its own
+the IMAGERY and SINCE filters, and the panel hides each filter row no lit provider
+honours (`filterControls`). The viewer is Google's `StreetViewPanorama` in its own
 element in the viewer host, without Google's fullscreen, close and address
 controls (the address goes in the caption); a pose goes out at once and
 again when the panorama's month, photographer and address arrive (one
@@ -3567,8 +3698,7 @@ are no KartaView photos in it. A tile's lines are OSM way segments with
 photos and carry no sequence, date or projection, so `decode.js` chains
 segments that meet end to start (about four times fewer lines; linear time,
 at most 20,000 segments a tile and 5,000 points a line), they are
-drawn as `kv:line:<z/x/y/n>`, up to 1,600 per tile, and never highlighted
-(`highlightsSequence: false`, so the legend has no "Selected"), and the
+drawn as `kv:line:<z/x/y/n>`, up to 1,600 per tile, and never highlighted, and the
 provider declares `filters: ['pano', 'since']` and `coverageLabel` ("N
 streets in view · click a line for its nearest photo"). KartaView filters
 coverage only in its PNG tiles (`/sequence/tiles/{x}/{y}/{z}.png?fieldOfView=360|plane&startDate=YYYY-MM-DD`;
@@ -3577,8 +3707,7 @@ asked for), so a filtered tile is drawn from the cached JSON segments that
 lie on the filtered PNG's drawn pixels (`maskedSegments`: at least half the
 points sampled every 2 px have a drawn pixel within one; on Jakarta's 360°
 filter, 332 of 1,041 segments lie on it, 676 miss it, 33 fall between).
-A filter change reloads the lines (`lineCoverage.reload`: the drawn ones show
-until the new ones are in), keeps the JSON segments, and caches masks per
+A filter change reloads the lines (`lineCoverage.reload`), keeps the JSON segments, and caches masks per
 filter and tile. A dense filtered PNG can take KartaView over a minute the
 first time (it answers 504 at 60 s and keeps drawing), so a timeout or 5xx is
 asked again 4 s later, four tries in all; then the panel says it did not
@@ -3589,8 +3718,8 @@ lookup asks the photo API for the projection (`SPHERE`/`PLANE`; it ignores
 `fieldOfView`) and upload date and checks each answer the same way (when
 photos are near but none passes, the panel says so), and the cones pass on
 each photo's projection and upload date. The provider declares
-`sinceBasis: 'upload'`, so while it is lit the panel shows "KartaView: by
-upload date" under the SINCE slider (`sinceNote` in the UI state). Tiles come uncompressed and
+`sinceBasis: 'upload'`, so while it is lit the panel shows "(by
+upload date)" beside the SINCE value, as ANY DATE (by upload date) (`sinceNote` in the UI state). Tiles come uncompressed and
 uncacheable, so the last 24 decoded tiles are kept for 10 minutes while
 KartaView is lit (`createTileCache`, dropped when it is switched off); one
 that does not answer in 20 s is asked once more, and one that is not a line
@@ -3605,7 +3734,7 @@ remembered; a storage timeout or 5xx is asked again. The open photo's
 sequence draws as cones from the 250-photo page holding it
 (`/2.0/sequence/{id}/photos`); the panel counts the drive's own photos
 (`countActivePhotos`, asked once per sequence). The camera direction (the
-marker, cones, FOLLOW, and a panorama's centre) is the direction of travel
+marker, cones and a panorama's centre) is the direction of travel
 to the next photo a few metres on (`assignCourses`): KartaView is dashcam
 imagery, while its `heading` is the device compass, which reads 0 for whole
 drives without one and can sit a steady 110° off inside a car. Until the
@@ -3662,23 +3791,18 @@ to 30 km and z10 to 60 km, as Mapillary's (a dense z10 tile over Paris is
 line (Douglas–Peucker to the segment, 4 units of a 4,096 tile: about a
 pixel where it is drawn, 6–10% of a GPS track's points), and the tiles in
 view draw their longest lines within 90,000 points (`maxPoints`,
-`keepOrder`), shared out once loading settles so a sparse tile keeps all
-it has and a dense one (a city centre) takes the rest; the selected
-sequence is always drawn. Every point becomes ~8 ground-line vertices:
+`keepOrder`), split evenly between the tiles in view (10,000 points
+each). Every point becomes ~8 ground-line vertices:
 unsimplified, the lines hung the tab. Decoded tiles are kept while the
-provider is on (16, ten minutes, `tileCache.js`, shared with KartaView),
-and above
-60 km the `grid` layer's 0.1°
-density cells, binned to at most 96×96 points a tile (a z0 tile holds
-~70,000 cells) and not counted as sequences: the panel says to zoom in.
+provider is on (16, ten minutes, `tileCache.js`, shared with KartaView).
+Above 60 km nothing is drawn and the panel says to zoom in.
 A tile decodes in slices of about 8 ms, the page getting a turn between
 them (a 2 MB z10 tile is ~200 ms of work). A busy API (429/503) holds the
 tiles back for its Retry-After, which the browser cannot read here (the API
 exposes no headers), so the wait doubles from 5 s to 5 minutes until it
 answers; an answer may take as long as it keeps arriving (silent for 15 s
 is given up), so a slow link still gets its megabyte tiles. Both
-filters apply: lines carry their day and camera type, and a cell stays while
-it holds pictures of the kind asked for (cells are undated). A click on a
+filters apply: lines carry their day and camera type. A click on a
 line asks the core (`actions.openNearest`) for that sequence's picture
 nearest the click, within the camera height / 100 (50–400 m: from high up
 a click lands well off a line), without framing, then any sequence's within
@@ -3727,8 +3851,9 @@ runs against real Mapillary and needs `MAPILLARY_CLIENT_TOKEN`. `npm run
 qa:street-level:fixtures -- --url <server>` answers every Mapillary request
 from fixtures (`providers/mapillary/coverageFixture.mjs`,
 `scripts/fixtures/street-level/`), and KartaView's and Panoramax's too, so it
-needs no network and covers the whole photo flow. CI runs the fixture gate and `qa:panel-resize`
-against a production build served by `vite preview` with a dummy token.
+needs no network. It opens and closes a photo from Mapillary, KartaView and
+Panoramax; stepping, EXPAND, FIT/FILL, the filters and Street View stay with
+the unit tests. CI runs the fixture gate against a production build served by `vite preview` with a dummy token.
 
 Directions is a keyless front end to the routing the voice agent already
 uses. Its row chips are the whole interface: DRIVE / WALK / BIKE pick the
@@ -4366,7 +4491,7 @@ 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. Manual calibration only —
+  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 —
   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
@@ -4384,12 +4509,14 @@ 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). Coverage is now **metro-wide: 250 cameras** (`CCTV_AUSTIN_MAX_SOURCES`
+  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`
   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 keyless highway cameras including Kitchener-area routes
-  (cap 1,000, all enabled rows from the current ~944-camera catalog). All sources are RAW PRIOR
+  sources. Ontario 511 (2026-09-12) adds highway cameras including Kitchener-area routes
+  (cap 1,000, all enabled rows from the current ~944-camera catalog). The 511on.ca API now
+  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.
   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
@@ -4397,7 +4524,18 @@ silently demoting every later lookup for the session.
   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.
+  ~1,100 cameras total, all RAW PRIOR poses, stills-first. The catalog lives for 15 minutes; once
+  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.
+  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
@@ -4714,7 +4852,7 @@ 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). `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.
+  - **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.
   - **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.
@@ -5021,7 +5159,7 @@ pins and share links already supply complete boxes.
   Pixel-mode pinch deltas receive bounded amplification before reaching the
   canvas; ordinary wheel, line/page-mode and native touch-pinch paths are left
   unchanged. The application scene owns and removes the relay listener.
-- Z ladder: panels promote within 100–139 (renormalized on wrap), voice pill 150, toast 200, clean-view exit 300.
+- Z ladder: panels around 100, voice pill 150, toast 200, clean-view exit 300.
 - Panel POSITION keys are versioned `v8` (`godsEyeView.v8.panelPos.<id>`); collapsed-state keys remain `v6`. The one-time position reset clears stale DISPLAY placements that could overlap the Context rail.
 - Map Source lives in the bottom Visual Presets tray. The left accordion contains no MAP STACK panel, and the `k` panel token that addressed it is gone from the share registry, so legacy `ui=k...` state takes the ordinary unknown-token skip.
 - A dock popover (Visual Presets, Location) auto-dismisses on mouse-away unless pinned. Focus inside the tray defers that dismissal only when the browser reports `:focus-visible` — keyboard focus and typed-into fields hold the tray open; a mouse-clicked tile does not, because Chromium focuses a `<button>` on press.
@@ -5232,8 +5370,8 @@ easier to meet (detection is now on more often), but does not create it.
   samples and constant elevation during E/N drag; one shared-floor resolution on
   release; late one-shot shared-cell work is permitted during viewshed idle. The
   A+B harness intentionally excludes citywide LOD assertions.
-- Panel positions have a versioned storage name, `godsEyeView.v8.panelPos.<panel-id>`. Docked panels store nothing; a portable panel (CCTV, Street Level) stores `{ left, top, width, height, floating: true }` once a header drag lifts it out of the rail, and a header double-click removes it. Double presses are detected in the header's `pointerdown` handler, because its `preventDefault()` suppresses native `dblclick`. Collapsed state persists for every panel at `godsEyeView.v6.panelCollapsed.<panel-id>` (`'0'` open, `'1'` closed, absent means the panel's own default).
-- Legacy draggable-panel position keys may remain in local storage for backward compatibility, but the map-mode right rail ignores them unless they describe a portable panel's floating window; collapsed states still persist at `godsEyeView.v6.panelCollapsed.<panel-id>`.
+- Panel positions have a versioned storage name, `godsEyeView.v8.panelPos.<panel-id>`, but the current rails lay panels out adaptively and write none. Collapsed state does persist for every panel at `godsEyeView.v6.panelCollapsed.<panel-id>` (`'0'` open, `'1'` closed, absent means the panel's own default).
+- Legacy draggable-panel position keys may remain in local storage for backward compatibility, but the map-mode right rail ignores them; collapsed states still persist at `godsEyeView.v6.panelCollapsed.<panel-id>`.
 - Flight/military tracked entities cache dead-reckoned positions per frame to avoid callback desync flicker.
 - Aircraft 3D-model and tracking invariants are covered by `npm run test:track`; run this before touching `flights.js`, `militaryFlights.js`, `detection.js`, or `trackedReadout.js`.
 - Annotation resolver behavior is pinned by `src/annotations/annotationResolver.test.mjs`; re-run that suite before changing place-resolution scoring.

docs/KNOWN-ISSUES.md

@@ -57,9 +57,8 @@ Related keys (current versions):
 - Panel collapsed state: `godsEyeView.v6.panelCollapsed.<panel-id>` — `'0'` open,
   `'1'` closed, absent means the panel's own default. A view opened from a share
   link ignores the stored value entirely.
-- Panel positions: `godsEyeView.v8.panelPos.<panel-id>` — written only for a
-  floating portable panel (CCTV, Street Level). Deleting it, or double-clicking
-  the panel header, docks the panel again.
+- Panel positions: `godsEyeView.v8.panelPos.<panel-id>` — the current layout
+  writes none.
 - CCTV calibration: `godsEyeView.cctv.calibration.v2`
 
 ---

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 |
+| `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 |
 | `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 |
+| `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 |
 | `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

@@ -1,22 +0,0 @@
-# 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

@@ -1,58 +0,0 @@
-# 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

@@ -1,679 +0,0 @@
-#!/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

@@ -1,527 +0,0 @@
-#!/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

@@ -1,62 +0,0 @@
-# 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

@@ -1,26 +0,0 @@
-<!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

@@ -1,53 +0,0 @@
-{
-  "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

@@ -1,14 +0,0 @@
-{
-  "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

@@ -1,916 +0,0 @@
-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

@@ -1,72 +0,0 @@
-// 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

@@ -1,296 +0,0 @@
-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

@@ -1,512 +0,0 @@
-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

@@ -1,323 +0,0 @@
-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

@@ -1,832 +0,0 @@
-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

@@ -1,218 +0,0 @@
-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

@@ -1,154 +0,0 @@
-// 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

@@ -1,79 +0,0 @@
-"""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

@@ -1,107 +0,0 @@
-"""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

@@ -1,495 +0,0 @@
-"""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

@@ -1,288 +0,0 @@
-"""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

@@ -1,188 +0,0 @@
-"""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

@@ -1,571 +0,0 @@
-"""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

@@ -1,40 +0,0 @@
-// 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

@@ -1,511 +0,0 @@
-#!/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

@@ -1,406 +0,0 @@
-#!/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

@@ -1,42 +0,0 @@
-#!/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

@@ -1,33 +0,0 @@
-#!/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

@@ -1,133 +0,0 @@
-#!/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

@@ -1,28 +0,0 @@
-#!/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

@@ -1,172 +0,0 @@
-#!/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

@@ -1,31 +0,0 @@
-#!/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

@@ -1,38 +0,0 @@
-#!/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

@@ -1,23 +0,0 @@
-#!/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

@@ -1,26 +0,0 @@
-#!/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

@@ -1,175 +0,0 @@
-"""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

@@ -1,205 +0,0 @@
-"""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

@@ -1,78 +0,0 @@
-"""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

@@ -1,32 +0,0 @@
-[
- {
-  "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

@@ -1,69 +0,0 @@
-"""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

@@ -1,109 +0,0 @@
-"""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

@@ -1,132 +0,0 @@
-"""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

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

intro-sequence/tools/imagery/build_clouds.py

@@ -1,76 +0,0 @@
-"""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

@@ -1,91 +0,0 @@
-"""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

@@ -1,133 +0,0 @@
-"""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

@@ -1,20 +0,0 @@
-"""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

@@ -1,15 +0,0 @@
-"""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

@@ -1,116 +0,0 @@
-"""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

@@ -1,82 +0,0 @@
-"""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

@@ -1,15 +0,0 @@
-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

@@ -1,76 +0,0 @@
-"""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

@@ -1,72 +0,0 @@
-"""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

@@ -1,21 +0,0 @@
-"""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

@@ -1,53 +0,0 @@
-"""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

@@ -1,15 +0,0 @@
-#!/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

@@ -1,91 +0,0 @@
-// 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

@@ -1,19 +0,0 @@
-# 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

@@ -49,7 +49,6 @@
     "test": "node scripts/run-unit-tests.mjs",
     "test:track": "node scripts/track-regression.mjs",
     "qa:map-source-tray": "node scripts/qa-map-source-tray.mjs",
-    "qa:panel-resize": "node scripts/qa-panel-resize.mjs",
     "qa:street-level": "node scripts/qa-street-level.mjs",
     "qa:street-level:fixtures": "node scripts/qa-street-level.mjs --fixtures",
     "check:boundaries": "node scripts/check-import-directions.mjs && node scripts/check-package-boundaries.mjs",
@@ -277,6 +276,7 @@
     "./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"
   }
 }