DemandSupplyForecast.as_dict() не эмитил 'confounded'/'is_confounded_window',
report_assembler._confounded() всегда возвращал False и §15 confounded_window
factor в compute_report_confidence был мёртв: 48-мес окна, пересекающие
2024-07-01 шок никогда не тянули report confidence к 'low' и шок не назывался
в rationale.
Patch: добавлено confounded: bool в DemandSupplyForecast (от §9.5 macro_coef
OR §9.6 rate_sensitivity), exposed в as_dict(). _confounded() уже использовал
.get() defensively — блокер был в producer'е.
+3 теста: contract на real DemandSupplyForecast.as_dict(), end-to-end
assemble_report → confounded_window factor surfaces at level=low, weakest-link
тянет overall к 'low'. 61 report_assembler + 1034 forecasting тестов зелёные.
Closes#1222
deficit_index pins to -1.0 for every ЕКБ segment (12mo demand flow vs multi-year
supply stock → log-ratio clamps) → zero discriminating power, though the oversupply
is partly real. Add MOI (gross competing supply / demand_per_mo), the real-estate
absorption standard, as an additive non-saturating companion that DISCRIMINATES
(Уралмаш 42mo … Чермет 109mo) where deficit cannot. deficit_index math kept exactly
as-is (honest absolute: -1 = genuinely oversupplied); docstrings clarify -1 is common
and MOI is the discriminating companion (no recalibration). _gross_supply extract-method
(single source of truth; _project_supply behavior byte-identical, code-review-verified).
Surface MOI in §22 future_market (passthrough) + exec_summary key_numbers/verdict.
Guards: no demand → None, no supply → 0. Prod: MOI varies 42→109mo, deficit stays -1.
Discrimination test pins MOI separating two segments both at deficit -1. Refs #952.
Found by read-only services audit.
- recommendation._usp_from_deficits: skip di<=0 so «стройте его» is never emitted
for OVERSUPPLIED formats; all-surplus top-K → [] (no white-space niches).
Aligns with product_scoring._count_positive_usp (di>0). Was: «Дефицит формата
X — стройте его» for a surplus format, reaching PDF/Excel USP-ниши.
- report_assembler._domrf_coverage: drop ambiguous >1.0 percent-guess; normalize
per-branch (analyze pct /100, supply_layers fraction as-is). Sub-1% coverage
(0.8%) no longer read as 80% → no inflated confidence in the near-zero-coverage
case §15 flags. tests for both + end-to-end no-inflation. 241+148 pass.
