The old test_no_program_reproduces_greedy_output_unchanged only compared
building_program=None (default) vs explicit None — both through the new
_Placer code — so it proved the two None branches agree but did NOT pin
the greedy geometry; it would still pass if the _Placer extraction had
drifted the output. test_placement.py only checks invariants, never
concrete counts/TEAP, so there was no anti-regression guard that the
greedy path is byte-identical after the refactor.
Replace it with two tests:
- test_greedy_output_matches_golden_pin: hard-coded literals per strategy
on the fixed _BIG_PARCEL — (features, built_area_sqm, total_floor_area_sqm,
apartments_count) — frozen from the current (== pre-refactor) output, so
any future deterministic drift in greedy placement FAILS.
- test_explicit_none_program_equals_default_greedy: keeps the None-branch
equivalence check (default vs explicit None go one greedy path).
Extend the concept generator so ConceptInput can carry an optional
building_program (list of typed houses from a catalog). When present,
placement lays out EXACTLY that program — for each item, place `count`
sections of the catalog footprint at the item's floors — instead of the
greedy max-FAR coverage-cap sweep. When absent, the existing greedy
behavior is unchanged (byte-for-byte backward-compatible).
- catalog.py: hardcoded HOUSE_TYPES (panel_econom, monolith_comfort,
tower_business, lowrise_comfort, townhouse) — sane-default catalog,
promote to DB later; get_house_type / available_section_types lookups.
- schema: additive BuildingProgramItem {section_type, floors, count} and
ConceptInput.building_program (default None -> greedy). ConceptVariant
gains optional placed_count / requested_count (partial-fit signal).
- placement: shared _Placer (collision/STRtree/setback machine extracted
from greedy sweep, reused — no duplication); place_program +
place_program_variant; branch in place_all_strategies on
building_program. Mixed-floor TEAP via exact per-floor-group aggregation
(GFA = sum(area_i * floors_i), no rounding drift).
- partial fit: when the parcel can't fit all sections, place as many as
fit and report placed_count < requested_count (no hard-422); zero-fit
still raises ParcelGeometryError (-> 422).
- API: validate program section_type keys against the catalog (unknown ->
422) before placement.
- tests: catalog integrity, greedy backward-compat, exact 2-item program +
TEAP reflection, over-packed partial placement, API program path.
- regenerate frontend api-types.ts (OpenAPI codegen gate stays green).
Stage 2a of epic #1953: backend service + endpoint for live economic recompute
driven by the interactive 3D massing (Stage 2b debounced sliders).
- teap.py: add pure synthesize_teap_from_program(total_footprint_sqm, floors,
site_area_sqm, housing_class, sections) — builds a TEAP from the SCALAR
aggregate footprint × floors, mirroring synthesize_teap_from_buildability and
reusing the same shared norm constants (_OFFICE_SHARE_OF_GFA / _EFFICIENCY_BY_CLASS
/ _AVG_APARTMENT_SQM / _PARKING_PER_APARTMENT) — single source of truth.
- schemas/concept.py: add MassingProgram (program contract, optional pre-resolved
market_price_per_sqm + parcel_centroid_wkt) and MassingRecomputeOutput (teap + financial).
- api/v1/concepts.py: add POST /api/v1/concepts/recompute — synthesize TEAP → run
the existing pure compute_financial. FAST path uses body market_price_per_sqm
(no DB); else _lookup_market_price by centroid via run_in_threadpool; else class norm.
- tests: synthesize_teap_from_program (gfa math, parity with compute_teap, class
efficiency, sections no-op) + endpoint (200, coherent output, price passthrough
skips DB, DB fallback, class-norm default, floors validation).
smr/sale_inflation_annual in _build_monthly_cashflow, gated by module constants =0.0 → byte-identical zero-diff (deep-review verified IEEE-754 identity + all 57 prior tests unchanged). Land not escalated; marketing/VAT/tax retimed on escalated revenue (total preserved). Capability wired+tested, OFF until calibrated indices + invariant reframe. No schema/codegen. Refs #1881
VAT charged on full gross margin → only on parking value-added; residential (реализация жилья + услуги застройщика по ДДУ) exempt per пп.22/23.1 п.3 ст. 149 НК; input VAT embedded in gross СМР. Σ cashflow == net_profit invariant preserved. PDF + concept-UI caveats synced. +3 tests, deep-review ✅.
Refs #1881
Финмодель брала фиксированное окно продаж 30 мес независимо от рынка
(schedule_is_default всегда true). Теперь окно считается из ЛОКАЛЬНОГО темпа
поглощения, который уже вычисляется в том же /analyze, но финмодель его
игнорировала.
Корректность абсорбции (ключевое): velocity.monthly_velocity_sqm — это СУММА
поглощения ВСЕГО конкурентного набора в радиусе (м²/мес), НЕ темп одного
проекта. Поэтому per-project absorption = monthly_velocity / max(n_with_sales,1)
(темп одного типичного локального продавца) — иначе модель считала бы, что новый
проект забирает весь рыночный темп (дико оптимистично). Поле
project_absorption_sqm_per_month добавлено в VelocityResult (objective-путь);
rosreestr-fallback и вырожденные пути → None (поквартальный count без
по-проектной декомпозиции не может задавать график).
financial.py: окно = clamp(ceil(residential/velocity), MIN=6, MAX=120) при
конечной velocity>0; иначе дефолт 30. Эскроу-инвариант сохранён:
sales_end=max(sales_start+base, constr_end). Инвариант Σ cashflow == net_profit
держится (перенос выручки во времени не меняет сумму). schedule_is_default
флипается в false когда график рыночный; новое поле sales_duration_months
(реализованное окно) для UI/PDF.
Wiring: parcels.py → synthesize_parcel_financial(velocity_sqm_per_month) →
compute_financial(market_velocity_sqm_per_month). Generative §1c путь пока
передаёт None (out of scope, follow-up).
Тесты: +13 (None→дефолт+инвариант; рыночная velocity; клампы MIN/MAX; эскроу;
non-finite→fallback; rosreestr→None; инвариант по размерам окна; регресс PR-3 —
ровно одна смена знака на коротком окне). Полный бэкенд: 3414 passed, 0 failed.
ruff+mypy(strict financial.py) чисто. api-types перегенерены.
Code-review: 2× approve, 0 majors (adversarial correctness-lens подтвердил
семантику абсорбции, инвариант, не-proxy IRR, клампы, rosreestr-None).
Refs #1881
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
