Commit Graph
138 Commits
Author SHA1 Message Date
grabowski a0086086a2 feat: rolling-origin event-aware evaluation harness for model variants
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One fold per monsoon season (train <= 30 Apr, test Jun-Nov, 2021-2025)
replaces the single fixed holdout that contained only ~4 warning events.
Metrics are what matters operationally: sustained first-alert lead vs
each observed 3.70m crossing (two consecutive alerting samples required;
lookback floored at the previous event's end so multi-peak floods can't
launder lead credit), peak error from the prediction actually issued 24h
before the peak (3h match tolerance, null on outages), false-alarm
episodes (12h gap tolerance), MAE / flood-regime MAE, and a Brier score
on warning exceedance — included because sigma cancels algebraically in
any p>=0.5 alert metric, so lead times compare predictors while Brier
compares uncertainty models.

Variants: baseline_abs (current), rise (target = future max - current
level), rise_weighted (flood-regime sample weights 1x->5x), and
rise_quantile (q50/q90 heads, spread-implied sigma). Harness verified by
a 3-agent adversarial review (features bit-identical across fold
cutoffs; three metric flaws found and fixed before first use).

Also: features.build_labels/build_matrix gain stats_end so the rescue
quantile is computed from pre-cutoff data only, closing the label-
construction leak flagged in the earlier ML review.
2026-08-12 15:19:26 +07:00
grabowski 98023243af feat: forecast precompute + issued-forecast archive + dashboard overlay
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The collection-leader worker now precomputes forecasts after every
scrape cycle: primes the /forecast cache (users never trigger the
multi-second inference — its TTL rises to 4500s so the hourly refresh
always wins) and persists every issued forecast to a new
forecast_history table keyed by (as_of, station, horizon) with
predicted max level, warn/danger probabilities, current level, and
model_version. This is the operational record the backtests lacked —
predicted-vs-actual becomes a simple join instead of retraining
historical models.

GET /api/forecast/history/{station} serves the archive (hours or
start/end + horizon filters, 5-min edge cache), and the station history
chart overlays 'Model 24 h peak (as issued)' as a dashed violet line
once data accumulates.
2026-08-12 14:13:39 +07:00
grabowski 731f10910e perf: stale-while-revalidate caching, bigger executor, cheap DB health probe
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Third on-box run: p50s healthy everywhere but tails at 60s — when a TTL
expired under load, every concurrent miss parked an executor thread on
the single-flight lock, exhausting the ~12-thread pool and timing out
unrelated endpoints. All cached endpoints (latest, HII, stats, health)
now use _cached_swr: fresh -> inline; expired-but-present -> the stale
value is returned immediately and ONE background task refreshes; only a
cold key (first request since startup) waits. Plus: dedicated
ThreadPoolExecutor (EXECUTOR_THREADS, default 48) replaces the cpu+4
default, and DatabaseHealthCheck no longer re-runs the CREATE TABLE DDL
suite on every probe (connect only when no live engine).
2026-08-12 12:32:38 +07:00
grabowski 96fedb3991 perf: single-flight /api/stats; fast-fail health probe
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The on-box rerun after the inline fast path showed the cached endpoints
healthy (latest p50 72-160ms, HII ~100ms) but /api/stats at 81% timeouts
and /health at 33%: stats had a cache but NO single-flight, so every
concurrent miss ran the heavy whole-DB counts (~1.7M rows) in parallel,
re-jamming Postgres and the executor — which also dragged uncached
history windows into 60s timeouts. /api/stats now computes through
_ttl_cached_stale (one computation per 5min TTL, stale served on
failure). The health API probe fails fast (5s instead of 30s) and its
cache TTL rises to 30s, so a slow upstream can no longer pin executor
threads longer than the cache lifetime.
2026-08-12 11:55:49 +07:00
grabowski 0b14e394ad perf: Cache-Control headers so browsers and edge caches absorb traffic
Bandwidth diagnosis: iperf shows the proxy<->API VPN link at 65-78
Mbit/s and a fast client pulls 15.7 MB/s from a CDN but only ~66 KB/s
from the site — the Caddy host's public uplink is the scarce resource.
Max-ages mirror the server cache TTLs (latest 30s, HII 60s, forecast
120s, history/stats/stations 300s, static 1h, dashboard HTML 120s), so
repeat views come from browser cache and an edge proxy (e.g. Cloudflare
free tier in front of Caddy) can serve most traffic without touching
the uplink.
2026-08-12 11:51:43 +07:00
grabowski d9c65bcf0c perf: inline cache fast path; cache /health checks
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The on-box load test exposed the real stall: cache HITS were dispatched
through asyncio.to_thread, so under load a microsecond lookup queued
~11s behind slow work in the ~8-thread default executor (endpoints
answered inline — /forecast 4ms, /api/stats 2ms — while every to_thread
endpoint sat at p50 8-17s). Handlers now check TTL caches inline in the
async path via _cache_fresh() and only pay for a thread on a miss.

/health results are cached for HEALTH_CACHE_TTL_SECONDS (10): its
external RID-API probe plus DB query were occupying executor threads on
every hit, which is what jammed the pool in the first place.
2026-08-12 11:48:05 +07:00
grabowski 1ec5cfb4df perf: gzip responses; multi-worker serving with single collection leader
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GZipMiddleware (min 500 bytes) compresses the dashboard HTML ~4x and
station JSON up to ~100x, end-to-end through the Caddy TLS terminator —
production load testing showed the deployment is bandwidth-bound once
the response caches hit, so compression is the capacity lever.

WEB_WORKERS (default 2) runs uvicorn multi-process via the app import
string. Every worker executes the lifespan, so a localhost lock port
(COLLECTION_LEADER_PORT, default 8901) elects exactly one
background-collection leader per machine — RID/HII polling stays
once-per-cycle instead of once-per-worker; the lock releases with the
process. Locust clients now send Accept-Encoding so future runs measure
compressed transfer, as browsers do.
2026-08-12 11:34:12 +07:00
grabowski 039af8caac perf: cache /measurements/latest; stale-on-error fallback for cached endpoints
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The response caches (HII feeds, and now /measurements/latest at 45s TTL
— the endpoint every dashboard poll hits) share one helper,
_ttl_cached_stale: single-flight per key, empty results never cached,
and expired entries kept as a fallback. If a recompute fails (DB
unreachable), the last good response is served with an X-Data-Stale:
true header instead of a 5xx — during an outage the dashboard keeps
showing the last real readings with their honest timestamps. TTLs:
LATEST_CACHE_TTL_SECONDS (45), HII_CACHE_TTL_SECONDS (120).
2026-08-12 11:05:02 +07:00
grabowski d27ca8bf40 perf: 120s TTL cache with single-flight on /api/hii/*/latest
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These endpoints ran an uncached latest-per-station aggregation on every
request (p50 0.6-0.9s under load, ~30% of the traffic mix) for data the
collector refreshes hourly. Responses are now cached per (feed, hours)
for HII_CACHE_TTL_SECONDS (default 120) with a per-feed compute lock so
a cache miss runs one query regardless of concurrency; empty results are
never cached so recovery is immediate. Cached hits measure ~8ms. Cache
is process-local behind a single helper — the seam where a shared
backend (Redis) would slot in if the deployment ever moves to multiple
workers; not warranted at one.
2026-08-12 10:58:19 +07:00
grabowski 0005f7dce1 feat: codified backtests, honest docs, belt-and-braces serving, perf fixes
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Retrained on the gap-filled DB (592k -> 976k rows) and re-examined the
flood backtests, now reproducible via scripts/backtest_render.py (renders
the three docs/img charts and gates on a >=12h 2024 first-alert lead —
currently failing by design and documented as such).

Findings, all documented in FLOOD_FORECASTING.md: the true 2024 crossing
was 24 Sep 17:00 (8h earlier than recorded; confirmed against the
independent HII sensor), the historical 24h-warning claim was partly a
missing-data artifact, and retrained warn classifiers collapse on the
filled grid (P.1 24h PR-AUC 0.900 -> 0.288) while regression MAE improves
(11.3 -> 10.5 cm). Serving therefore becomes max(classifier,
sigmoid(regression)) so alerting is never worse than the regression path;
metrics table, head-gating tiers, honest-limits and runbook expectations
all updated to the current model (hgb-v1+d2d0e65).

Perf, from Locust load testing (scripts/locustfile.py + load_test.py):
single-flight lock around /forecast inference (concurrent cache misses
previously each ran ~18s inference and starved the shared thread pool;
200-user run after: 105 rps, 0.01% errors), and /measurements/latest +
/health moved off the event loop (synchronous DB/network calls in async
handlers were stalling every request under load).
2026-08-12 10:46:00 +07:00
grabowski d2d0e655aa fix: All-time range fills the date pickers with the DB's first record date
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Uses first_timestamp from /api/stats (2018-08-01 fallback) as the start
date and today as the end, instead of clearing the pickers.
2026-08-11 17:02:31 +07:00
grabowski b89c7e1915 feat: flood-verdict banner, violet rain palette, per-station bands, chip contrast, Umami
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UI/UX review backlog round 2 plus analytics:
- at-a-glance verdict banner (role=status, aria-live) above the tiles:
  ok/watch/danger from P.1 level vs the official 3.70 m stage and the
  24 h forecast, with a not-an-official-warning disclaimer + ThaiWater
  link (also added to the forecast card)
- rainfall dots switch to a violet sequential ramp so they can never be
  confused with flow-status colors; legend gains 'Other markers' rows
  (grey no-data gauges, + bank-height sensors)
- history-chart flood bands now use each station's own /forecast
  thresholds (P.1 official fallback) instead of hardcoded 3.0/4.5
- chipStyle(): contrast-safe text on all code/risk/stage chips (dark ink
  on amber/ochre, darkened fills for white ink); risk/stage ramps drop
  the blue step for a monotonic green-ochre-amber-red escalation
- plain-language tooltips on the flow and capacity tiles
- Umami: client script tag plus opt-out server-side middleware posting
  api-request events (fire-and-forget, 3 s timeout, never blocks)
2026-08-11 16:56:53 +07:00
grabowski 5848621c77 fix: UI/UX review round 1 — mobile reachability, legend toggle, replay correctness
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From the multi-lens review (27 confirmed findings; this lands the quick
high-impact set):
- mobile: side-card cap 400px->70vh so the basin-stations expander is
  reachable; live-pill kept as a dot (title carries the label); replay
  button no longer wraps; legend returns behind a Legend toggle button
  (was display:none, which also removed the only rain toggle)
- replay: auto-refresh skips while replaying (was clobbering state);
  Chiang Mai flow tile shows P.1 replay discharge instead of a
  basin-wide sum mislabelled as P.1
- history: placeholder text in the empty chart, dropdown flips to
  'Custom range' when dates are hand-edited, controls hint when no
  station is selected
- a11y/copy: aria-expanded/aria-controls on all three disclosure
  controls, sensor rows say 'of bank height' vs tile 'channel capacity',
  P.1 tile note deduped
2026-08-11 16:39:53 +07:00
grabowski 09c1c84153 feat: search-engine indexing — robots.txt, sitemap.xml, llms.txt, SEO meta
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robots.txt (sitemap pointer, /metrics and /scrape/ disallowed),
sitemap.xml (/ and /docs), and llms.txt (site + API summary for LLM
crawlers) served at the domain root. Dashboard head gains title with
keywords, meta description, canonical, Open Graph/Twitter tags,
schema.org WebApplication JSON-LD, theme-color, and an inline SVG
favicon (also silences the /favicon.ico 404).
2026-08-11 16:33:44 +07:00
grabowski bd3353e2dc feat: buildfor.life link in dashboard footer
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grabowski d0018d6529 feat: physically meaningful stat tiles + footer links
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'Combined discharge' summed sequential mainstem gauges, counting the
same water several times — replaced with Chiang Mai river flow (P.1
discharge + % of channel capacity). 'Strongest flow' becomes 'Most
stressed gauge' (max discharge_percent basin-wide). Reporting-stations
note shows the ThaiWater/HII station count. Footer links to the source
repo and /docs API reference.
2026-08-11 16:25:41 +07:00
grabowski df31de092b fix: collapse additional-stations list by default; no scroll-jump on station click
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The 97-row ThaiWater/HII list was starving the RID flow list down to one
visible row. The section header is now a click/keyboard toggle (collapsed
by default, arrow indicator); searching auto-expands it so hidden
stations stay findable, and the flow list keeps a 280px minimum when
both are open. Selecting a station no longer scrollIntoViews the
history card.
2026-08-11 16:15:34 +07:00
grabowski e27d418a1a feat: station search in side panel; DB stats cover HII tables
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A search box above the station lists filters both the RID flow list and
the basin-station list by code, name (Thai included), or river, and
persists across refreshes. /api/stats now reports whole-DB totals — RID
+ hii_rainfall + hii_waterlevel counts, combined station count, and a
date range spanning all sources — with per-source breakdown fields the
stats strip shows as tile notes. Sensor section renamed to 'Additional
basin stations · ThaiWater/HII'.
2026-08-11 16:06:39 +07:00
grabowski ba4710b243 feat: 'Last N' labels on history ranges; dropdown mirrors into date pickers
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Quick-range options read 'Last 24 hours' … 'Last 90 days'; choosing one
fills the from/to date inputs with today and today-N (All time clears
them). Dropdown-driven loads still fetch the precise trailing-hours
window; hand-edited dates take over via state.useDates.
2026-08-11 15:58:28 +07:00
grabowski 9516857d44 feat: date-range picker on the station history panel; drop PostgreSQL naming
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/measurements/history/{code} accepts optional start/end date params that
override the hours window (end date inclusive). The dashboard history
card gains from/to date inputs beside the quick-range dropdown —
explicit dates win, changing the dropdown clears them. All user-facing
'PostgreSQL history' labels renamed to 'Station history'.
2026-08-11 15:52:40 +07:00
grabowski d29d49eac7 feat: collapsible flood outlook (P.1 only by default) + dashboard fixes
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The flood-risk card now shows just the Chiang Mai P.1 outlook; the
per-station forecast grid collapses behind a Show/Hide expander. Fixes:
the rain-layer toggle was unclickable (.map-overlay pointer-events:none
now re-enabled on the legend), long HII station codes (MOU302, FOP015)
wrap inside their chips instead of clipping, and the sensor panel sorts
by bank percentage with no-data stations last.
2026-08-11 15:48:20 +07:00
grabowski 4f3f19f6db feat: rainfall + HII water-level layers on the dashboard
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New endpoints GET /api/hii/rainfall/latest and /api/hii/waterlevel/latest
serve the latest per-station rows from the hii_* tables. The map gains a
TWA-style rain layer: circle markers binned by TMD 24-h classes (blues
for light/moderate/heavy, site amber/red for very-heavy/extreme), with a
legend block and show/hide toggle. The ThaiWater sensor panel now
prefers the DB-backed HII feed (no API key required, 97+ stations,
ThaiWater storage-percent situation colors, gauge-datum conversion via
offset_msl) and falls back to the live /sensors/thaiwater passthrough.
2026-08-11 15:26:58 +07:00
grabowski d72496f404 feat: backfill hii_waterlevel from the HII waterlevel_graph archive
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scripts/backfill_hii_waterlevel.py walks the api-v3 waterlevel_graph
endpoint (hourly wl_msl + discharge, archive back to ~2019) in full-year
windows per station and upserts into hii_waterlevel. Defaults to the
RID-mirror and key stations; --stations/--all/--start/--end/--chunk-days
override. History upserts touch only wl_msl and discharge so colliding
live-snapshot rows keep storage_percent/situation_level. Idempotent and
safe to re-run.
2026-08-11 15:11:08 +07:00
grabowski 33d8baa8dd fix: composite (station_id, timestamp) PK on hii_* measurement tables
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TimescaleDB create_hypertable rejects tables whose primary key omits the
partitioning column; the surrogate id PK served no purpose, so use the
natural key directly.
2026-08-11 14:50:27 +07:00
grabowski 1845ef7203 feat: hourly HII/ThaiWater rainfall + backup water-level collection
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Poll the open api-v3.thaiwater.net public endpoints (rain_24h,
waterlevel_load), filter to the Ping basin, and persist to new
hii_rain_stations/hii_rainfall and hii_wl_stations/hii_waterlevel tables
(auto-created; sqlite/postgresql/mysql). Water levels stay in their own
tables since HII reports m MSL from a different station set; rid_code
maps mirrors like ridhydro_P.1 to P.1 and offset_msl converts MSL to
gauge datum. Runs every scraping cycle in web-api and continuous modes
(hourly cadence even during 1-minute RID retry), one-shot via
--collect-hii; docs/DATA_SOURCES.md catalogs all probed endpoints.
2026-08-11 14:44:53 +07:00
grabowski 7befc82ff5 feat: database stats on the dashboard via GET /api/stats
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New SQLAdapter.get_database_stats() aggregates totals, station count,
date range, and hourly-slot coverage in one query per dialect. The
endpoint follows the existing 503-guard/to_thread/TTL-cache pattern;
the dashboard gains a five-tile stats strip on the existing refresh
cadence. Coverage denominator is hour-truncated so off-hour endpoints
cannot push it past 100%; MySQL slot expression avoids % characters
that would break under pyformat bind interpolation.
2026-08-10 23:27:36 +07:00
grabowski 5e62ea529d feat: --fill-gaps all repairs missing data across the whole DB range
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Gap detection is now hour-granular: days with partial data (missing
hourly slots) are re-fetched, not just days with no rows at all. The
API's hour-24-is-next-midnight quirk is handled by re-fetching day D-1
when day D is missing its 00:00 slot. SQL adapters gain single-query
range and recorded-hours lookups; non-SQL backends fall back to the
old day-granular check.
2026-08-10 22:13:58 +07:00
grabowski 410faeddd5 fix: protect admin API endpoints; stop rejecting flood-peak measurements
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Security: POST/PUT/DELETE /stations, POST /scrape/trigger and GET
/config now require an X-API-Key header matching ADMIN_API_KEY.
Secure by default - with no key configured those endpoints return 503
instead of being open. Comparison via secrets.compare_digest. Dashboard
and read endpoints stay public.

Data: the validator rejected any measurement whose discharge_percent
exceeded 200 - which silently deleted the Oct 2024 record-flood peaks
(the river genuinely ran at 201-226% of channel capacity). The cap is
now 500%, and an out-of-range percent nulls that auxiliary field
instead of discarding the whole row (water level and discharge are the
data that matter). Surfaced by the user's historical backfill log.
2026-08-10 18:47:08 +07:00
grabowski 27fa292e09 docs: September 2025 flood render - deployed config, 24 h warning, peak within 7 cm
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Hour-by-hour chart of the 25-28 Sep 2025 event as forecast by the exact
deployed configuration (trained through 2024, event unseen): first alert
26 Sep 18:00, flooding began 27 Sep 18:00 (24 h lead), predicted peak
4.00 m vs actual 3.93 m. The near-miss 3.51 m crest on 26 Sep correctly
never alerted.
2026-08-10 18:35:55 +07:00
grabowski f0183faa62 feat: discharge-driven river animation speed, replay stat tiles, hourly doc render
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- river dash animation now flows at a speed continuously derived from
  each segment's discharge (period 260/(Q+45) s, clamped 0.5-5.5 s) via
  inline per-path animation-duration, so it updates live and per-frame
  during the replay (CSS speed classes removed - setStyle cannot change
  classes)
- the replay drives the Combined discharge and Strongest flow stat
  tiles each frame (marked '2024 replay'), restored on finish
- docs: hour-by-hour detection detail render (22-28 Sep 2024) showing
  the model alert at 24 Sep 01:00, flooding at 25 Sep 01:00, and the
  24 h warning between them; embedded with commentary
- Matrix alerts now link to https://water.buildfor.life/ (override via
  ALERT_DASHBOARD_URL), replacing the Grafana public dashboard link
2026-08-10 18:29:01 +07:00
grabowski 6112c681a7 docs: render of actual vs predicted through the 2024 flood; adaptive replay speed
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docs/img/backtest-2024-p1.png: observed P.1 level vs the 24h-ahead
predicted peak issued at each hour by a model trained only on pre-flood
data, with the warning-probability panel below (first alert 24 Sep
01:00, 24 h before flooding began). Embedded in FLOOD_FORECASTING.md's
headline-validation section with an honest reading, including the
~0.4 m peak under-prediction.

Replay pacing is now adaptive: 4 h/frame through quiet days, 2 h when
risk is elevated, 1 h (hour-by-hour) while the model is alerting or the
river is near/above flood stage - so viewers can watch the detection
sequence unfold.
2026-08-10 18:10:48 +07:00
grabowski 199b0e3483 feat: replay shows when the model would have detected and warned
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The 2024 snapshot now carries a model track: p_warning and predicted
24 h peak from HGB heads trained ONLY on pre-flood data (an honest
backtest, cutoff 2024-08-31), plus its calibration sigma. During replay:

- the map clock shows the system's state at each moment: 'model: no
  flood expected' -> 'elevated risk' -> amber 'MODEL ALERT - flooding
  within 24 h likely (predicted peak X m)' -> red 'FLOODING' once the
  river actually crosses stage 1. First alert fires 24 Sep 01:00, a
  full day before the water crossed the flood line on 25 Sep.
- the flood-risk outlook stage chips re-render each frame from the
  historic model prediction (sigmoid over the stage levels), so the
  whole outlook panel time-travels with the map.
2026-08-10 18:07:57 +07:00
grabowski d015420b66 feat: full-basin 2024 flood replay with clock and demo indicator
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The replay now drives the entire map from a 120 kB all-station snapshot
(static/flood-2024-all.json: 649 hourly frames x 16 stations of level +
discharge, forward-filled on an aligned grid):

- station markers recolor/resize per frame from historic discharge
- river segments restyle per frame (color/width from the same
  nearest-gauge grading as live mode)
- flood zones flood/recede from P.1's historic level
- a large clock overlay on the map shows replay date/time, P.1 level
  and total basin flow
- the LIVE DATA pill switches to an amber '2024 REPLAY' (or
  'SIMULATION' for the demo_level/demo_rise hooks) and back on finish
- replay end or stop restores the live view via a full dashboard reload

Replaces the P.1-only snapshot (flood-2024-p1.json removed).
2026-08-10 17:59:06 +07:00
grabowski 0b885e572d chore: gitignore .playwright-mcp browser artifacts
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2026-08-10 17:45:21 +07:00
grabowski 0672ea5ffa feat: Oct-2024 flood replay, simulation hooks, and static replay data
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- header button 'Replay Oct 2024 flood': animates the real Sep 15 -
  Oct 12 2024 P.1 hourly series (~45 s) through the flood-zone display;
  zones flood blue as the river climbs to the 5.30 m record and recede
  as it falls; click again to stop; restores live state when done
- replay reads a pre-extracted 15 kB static snapshot
  (static/flood-2024-p1.json, 335 frames) instead of pulling the 4.6 MB
  all-time history on every click; falls back to the history API if the
  snapshot is missing
- demo hooks for testing/presentations: ?demo_level=4.4 pins a simulated
  P.1 level, ?demo_rise=1 animates rising water to 5.30 m; both label
  the outlook line as SIMULATION with the real level alongside
2026-08-10 17:44:36 +07:00
grabowski c62a03e778 feat: flooded zones render as water and auto-surface
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When P.1's current level reaches a zone's trigger level the zone fills
water-blue (solid border, .62 opacity) instead of the amber risk ramp,
and the zone layer adds itself to the map automatically - no toggle
needed during an actual flood. A manual hide sets a session flag so
auto-show does not fight the user.
2026-08-10 17:22:27 +07:00
grabowski 711629682d feat: per-marker icon field for custom markers
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custom-markers.json entries accept an optional "icon" (any emoji,
default pin); seeded homes/office icons for the existing markers.
2026-08-10 17:20:12 +07:00
grabowski 7e7d244efa feat: add baan boe marker
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2026-08-10 17:19:31 +07:00
grabowski 786b8514ea feat: custom map markers with per-location flood-zone risk
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src/static/custom-markers.json holds user points of interest
({name, lat, lon, optional note}); the dashboard renders them as pin
markers whose popups show which inundation zone the point sits in, its
P.1 trigger level, and the live 24 h exceedance probability (ray-cast
point-in-polygon against the zone geojson; smallest matching zone wins).
Seeded with the owner's four properties.
2026-08-10 17:16:28 +07:00
grabowski a17509f3ea feat: replace digitized flood zones with owner-traced polygons
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The 7 Chiang Mai inundation zones are now hand-traced by the project
owner against the real basemap (cnx_flood.geojson), replacing the
scan-digitized approximation and its georeferencing error entirely.
Features are ordered zone 7 -> 1 so the earlier-flooding (smaller)
zones render on top of the wider extents in Leaflet.
2026-08-10 17:12:23 +07:00
grabowski 4f12360960 fix: shift flood zones 1.05 km south, anchored to Nawarat Bridge
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The P.1 marker (Nawarat Bridge, 18.7875) sat inside zone 2 near its top
edge, but the bridge IS Chang Khlan's northern boundary - the layer was
~0.0095 deg too far north (the district-centroid correction in c4e0fb6
overshot). Zone 2's north edge now lands at the bridge.
2026-08-10 16:47:14 +07:00
grabowski c4e0fb6bae fix: re-georeference flood zones and make them clearly visible
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The previous affine fit slid along the mostly north-south river (an
ill-conditioned direction) leaving the zones ~1 km south-west of their
true position. New approach: extract the scanned river band by color,
match it to the OSM Ping mainstem centerline by arc length (which pins
the along-river position), then correct residual translation using
known district locations cross-checked against the river residual
(533 m -> ~300 m median; Chang Khlan zone centroid now within 200 m).
Mountain-area artifacts are clipped away via the municipality hull.

Zones were also nearly invisible at fillOpacity 0.16 - base opacity is
now 0.38, rising with the live 24 h exceedance probability, and 0.72
with a solid red border once the river is at or above a zone's level.
2026-08-10 16:38:09 +07:00
grabowski f05289e628 fix: CI matrix to Python 3.11 only until pandas is upgraded
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pandas 2.0.3 has no cp312 wheels, so the 3.12 matrix leg fails during
dependency install. The deployment runs 3.11.
2026-08-10 16:15:32 +07:00
grabowski 3b919adc56 feat: vector flood-zone polygons replace the scanned-map overlay
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Digitize the 7 Chiang Mai inundation zones from the municipal map into
geojson polygons: pixels classified by legend color, vectorized via
marching squares, and georeferenced by a 6-parameter affine fitted
least-squares to the OSM Ping centerline (109 m median residual after
outlier-filtered refits - the scanned image overlay could never scale
correctly and is removed).

The dashboard renders the zones as a Leaflet geoJSON layer styled live
from the forecast: fill opacity scales with each zone's 24 h exceedance
probability, zones whose trigger level the river has already reached get
a solid red border, and each polygon's popup shows its trigger level and
live probability. Zone styles refresh with every forecast load.
2026-08-10 16:14:34 +07:00
grabowski 6c0bb024a8 chore: remove stray zero-byte files accidentally committed
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2026-08-10 15:57:19 +07:00
grabowski ecd34177bb fix: backtest/review findings in the flood-ML package
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From the adversarial review and threshold backtest (swarm verification):

- predict.py: when a bundle's trained thresholds differ from the current
  config (deploy before retrain), skip its stale classifier heads and
  derive p_warning/p_danger from the regression + sigma against the
  CURRENT thresholds - the dashboard can no longer show contradictory
  old-threshold classifier output next to new-threshold stages
- features.py: decouple the low-coverage regression-label rescue from
  the warning threshold (now the station's own p97.5 level); the old
  coupling silently dropped 34% of P.5's regression training rows and
  cost +46% MAE when its threshold rose
- features.py: P.82 danger 3.80 -> 3.75 (3.80 was above the station's
  8-year maximum of 3.78, so danger could never train or fire)
- data.py / predict.py: anchor models/cache paths to the repo root; the
  relative paths silently returned zero rows when run from another CWD
- annotate P.4A thresholds as low-confidence (11 supporting readings)

47 tests pass. Retrain required for the label-rescue and P.82 changes
to reach the classifier heads.
2026-08-10 15:57:01 +07:00
grabowski 9cac9c4d2a style: apply black/isort across the repo; make CI mypy advisory
The push-CI gates (black/isort/mypy) had never actually run before the
branch-trigger fix, and the codebase predates them. Formatting is now
black/isort clean repo-wide. mypy keeps running but non-blocking: 86
pre-existing errors are a separate cleanup, not a gate to hold hostage.
2026-08-10 15:57:00 +07:00
grabowski 300c0e0b6f fix: trigger CI on master (repo default branch), drop unsupported Python matrix entries
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Workflows listened on 'main'/'develop' but the repo's default branch is
master, so push events never started a job (every historical run is a
schedule event). Point push/PR triggers and the deploy-gate refs at
master, and trim the test matrix to 3.11/3.12 to match
requires-python >=3.11.
2026-08-10 15:46:24 +07:00
grabowski e4d5d274f0 feat: per-station flood thresholds and Chiang Mai inundation stages for P.1
Replace the network-wide (3.0, 4.5) m thresholds with per-station values
calibrated from the DB's discharge_percent (RID % of channel capacity):
warning = median level at 75-85% capacity, danger = median at 95-105%.
Fixes P.103 over-alerting (bank-full ~6.75 m, not 4.5) and P.67
under-alerting (overflow ~2.9 m). Requires a retrain to take effect in
the classifier heads.

P.1 uses the official Chiang Mai municipal inundation map instead:
warning 3.70 m (stage 1, city flooding begins), danger 4.20 m (stage 5),
with the full 7-stage table (3.70-4.60 m + discharge) in
features.P1_FLOOD_STAGES. Forecast rows for P.1 now include per-stage
exceedance probabilities computed from the regression head + calibration
sigma - available immediately without retraining.

Dashboard: "Chiang Mai city flood outlook" block above the forecast grid
(predicted peak + 7 stage-probability chips) and a toggleable
georeferenced overlay of the official flood-zone map
(static/flood-zones-p1.jpg, bounds tunable in FLOOD_ZONE_BOUNDS).
2026-08-10 15:35:00 +07:00
grabowski 29f4b5818d fix: require Python >=3.11 and lock scikit-learn deps for uv
scikit-learn 1.9.0 supports only Python >=3.11, so uv could not resolve
the >=3.9 range. The deployment runs 3.11. Also pins numpy back to
1.26.4 in the lockfile (pandas 2.0.3 ABI).
2026-08-10 14:44:54 +07:00