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Contains projects associated to the development of modeling products
647c1aad0e
RdSAP 10 §5.18 (PDF p.48) "Curtain wall - U-value and other parameters":
"If documentary evidence is available, use calculated U-value of the
whole curtain wall. Otherwise for the purpose of RdSAP, U= 2.0 W/m²K
for pre-2023 curtain walls, And for post-2023 (2024 in Scotland)
U-values as for windows given in Notes below Table 24."
Table 24 row "Double or triple glazed England/Wales: 2022 or later"
PVC/wood column = 1.4 W/m²K. Whole-wall curtain walls use Frame
Factor=1 per the §5.18 closer.
Pre-S0380.85 `WALL_CURTAIN=9` was defined at rdsap_uvalues.py:116 but
NOT included in `known_types`, so `u_wall(construction=9)` fell through
to `_DEFAULT_WALL_BY_AGE.get(band, WALL_CAVITY)` → cavity table at age
H = 0.60. Cert 000565 BP[2] Ext2 lodges `Type: CW Curtain Wall` +
`Curtain Wall Age: Post 2023` per Summary PDF §7; worksheet pins U=1.40
(matching the §5.18 Post-2023 PVC/wood row). Cascade under-counted
walls by Δ U=0.80 × area = −112.2 W/K on this BP — 70% of the
post-S0380.84 BP main-wall residual (−161 W/K total).
§5.18 keys the curtain-wall U-value on the per-BP installation age,
NOT on the dwelling-wide `construction_age_band` — cert 000565 is
age H (1991-1995) but the curtain wall itself was installed
Post-2023. Plumb a new optional field through the extractor → datatype
→ mapper → cascade so the §5.18 dispatch sees it.
Files touched (5-layer slice span):
- backend/documents_parser/elmhurst_extractor.py:
`_wall_details_from_lines` reads "Curtain Wall Age" via
`_local_val` so absent lines stay None (not "").
- datatypes/epc/surveys/elmhurst_site_notes.py:WallDetails:
`curtain_wall_age: Optional[str] = None` field added.
- datatypes/epc/domain/epc_property_data.py:SapBuildingPart:
`curtain_wall_age: Optional[str] = None` field added.
- datatypes/epc/domain/mapper.py:_map_elmhurst_building_part:
threads `walls.curtain_wall_age` onto SapBuildingPart.
- domain/sap10_ml/rdsap_uvalues.py:
new `_u_curtain_wall(curtain_wall_age)` helper + WALL_CURTAIN
dispatch in `u_wall` before the `known_types` lookup.
"Post 2023" / "Post-2023" → 1.4; everything else (incl. None)
→ 2.0 per §5.18 fallback.
- domain/sap10_calculator/worksheet/heat_transmission.py:
passes `curtain_wall_age=part.curtain_wall_age` to `u_wall`
on the main-wall path. (Alt-wall path unchanged — cert 000565
lodges CW only as a main wall, never as an alt sub-area; alt
coverage is a follow-up slice if a future cert exercises it.)
Tests (6 new, AAA-structure):
- 3 in domain/sap10_ml/tests/test_rdsap_uvalues.py — `u_wall` direct
unit tests for Post 2023 (1.4), Pre 2023 (2.0), and absent
lodging fallback (2.0).
- 3 in backend/documents_parser/tests/test_summary_pdf_mapper_chain
.py — extractor pin (BP[2] Ext2 surfaces "Post 2023", non-CW BPs
stay None), mapper pin (curtain_wall_age threaded to BP[2]
SapBuildingPart), cascade pin (`heat_transmission_from_cert`
walls subtotal ≥ 540 W/K — pre-S0380.85 was 443).
Cert 000565 cascade walls: 443 → 555.93 W/K (worksheet 604.07; 70%
closer). Test baseline: 558 pass (was 555 + 3 new) + 9 expected
`test_sap_result_pin[000565-*]` fails unchanged.
Per [[feedback-verify-handover-claims]]: the post-S0380.84 handover
predicted SH residual would close +2591 → ~+800 kWh after this slice,
but the cascade is actually OVER-counting SH despite walls being
UNDER-counted. Closing the wall under-count makes the SH residual
*larger* (+2591 → +6348). The wall fix is spec-correct; the SH
over-count is a separate channel that surfaces more sharply now. Per
[[feedback-spec-citation-in-commits]] + [[feedback-spec-floor-skepticism]]
+ the S0380.84 precedent, ship the spec-correct change and document
the surfaced gap for the next slice rather than reverting to the
compensating-bugs state.
Pyright net-zero on every touched file (existing pre-existing errors
unchanged). Cohort + golden + cert 9501 unaffected — curtain_wall_age
defaults to None on those certs and `u_wall` ignores it unless
`construction == WALL_CURTAIN`.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs/adr | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| scripts | ||
| sfr/principal_pitch | ||
| survey_report | ||
| tests | ||
| utilities | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| ara_backend_design.md | ||
| BaseUtility.py | ||
| CLAUDE.md | ||
| conftest.py | ||
| CONTEXT.md | ||
| devcontainer.sh | ||
| Dockerfile.test | ||
| Dockerfile.test.dockerignore | ||
| Makefile | ||
| MEMORY.md | ||
| package-lock.json | ||
| package.json | ||
| pyproject.toml | ||
| pyrightconfig.json | ||
| pytest.ini | ||
| README.md | ||
| run_lambda_local.sh | ||
| serverless.yml | ||
| test.requirements.txt | ||
| tox.ini | ||
| UBIQUITOUS_LANGUAGE.md | ||
Model Repository
This repository contains the code pertaining to the development of the data science and machine learning products being utilised by Hestia.
The different folders in this repository relate to services that can be used independently, or can be imported and used as part of a larger application
Getting Started
Prerequisites
Dev Container Setup
This repo uses a Docker Compose-based dev container. The model-backend service joins a shared-dev Docker network so it can communicate with other local services (e.g. a frontend container) running on your machine.
VS Code users: The initializeCommand in devcontainer.json creates the shared-dev network automatically before the container starts. No manual step required — just open the repo and select Reopen in Container.
Non-VS Code / CI workflows: Run the following once before starting the container:
make dev-setup
This is idempotent and safe to re-run if the network already exists.
Folders
backend/
This folder contains the code for the fastapi backend service, which provides an interface to much of the functionality in this repository, for the frontend
model_data/
This folder contains related to the reading and preparation of assessment model data, including pulling out epc attributes
Testing
All tests can be run, against the configuration in pytest.ini running
pytest
This will run the complete panel of tests and report on coverage in the locations specified by the pytest.ini file.
To run tests in a specific service, e.g. inside of model_data, simply run
pytest --cov-config=model_data/.coveragerc --cov=model_data
This will produce the test results and coverage reports