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3 commits

Author SHA1 Message Date
Emi Griffith
21f7ef4d19 Group regression tests by domain (#215)
Move the flat backend/tests/*.py into domain subfolders so the suite
mirrors the code's concerns:
  data/          climate, grading, scoring, grid, places, store
  web/           api, content, homepage, views
  notifications/ notify, digest, discord (+ dm/interactions/link)
  accounts/      api_accounts
  core/          metrics, singleton, dashboard

conftest.py stays at the tests/ root, so its sys.path setup and shared
fixtures still apply to every subfolder. The four tests that derive repo
paths from __file__ get their depth bumped one level to match their new
location. Pytest discovers the subfolders recursively; the CI command
(python -m pytest backend/tests) is unchanged.

Claude-Session: https://claude.ai/code/session_01XXxmNFy9cZ6Gh8Y9thZn62
2026-07-20 04:50:01 +00:00
Emi Griffith
a6dfa97bb0 Clarify wet bulb, add heat-stress-day share, frame total as net change (#197)
- Explain on the page what wet-bulb temperature measures (the evaporative-cooling
  ceiling on shedding heat), so the metric isn't opaque.
- Report the share of heat-stress "wet-bulb" days (peak wet bulb >= 26 C) vs
  normal days, recent window vs the full record — mirroring the precip wet-day
  frequency.
- Present the overall total as a direction-agnostic net change (magnitude only),
  not "warmer/cooler"; per-metric cards still carry direction.

Bumps the score cache version.
2026-07-19 23:37:42 +00:00
Emi Griffith
aec64b4058 Add a climate-score page from recent-vs-baseline percentile divergence (#196)
Score how far a location's last 6 years have drifted from its full 45-year
record. For each metric and percentile category (p10/p25/p50/p75/p90), the
recent-years value is placed on the baseline distribution and the gap from the
expected percentile is the divergence — unit-free, so metrics compare directly.
Scored per meteorological season plus annual, weighted into per-metric and
overall scores (temps, humidity and feels-like weighted heaviest).

- backend/scoring.py: divergence math, seasonal slicing, precip zero-inflation
  split (wet-day frequency + amount), tier mapping onto the existing temp scale.
- climate.py: derive a wet-bulb column (Stull 2011) at the read boundary, before
  the humidity column is converted to absolute — via a shared _derive_metrics
  wrapper at all four read sites.
- api/v2/score endpoint + build_score payload, cached on the history token with
  a scoring-version key.
- frontend score page: overall hero, per-metric cards, by-season chips, and a
  button-revealed summary (sentences + metrics×season table + per-percentile
  detail). Score nav link across all headers.
- Tests for the scoring math, wet-bulb formula, payload shape and route.
2026-07-19 23:02:33 +00:00