9458a03021
RdSAP 10 Specification §5.13 "U-values of exposed and semi-exposed
upper floors" (PDF p.47) + Table 20:
"Otherwise, to simplify data collection no distinction is made in
terms of U-value between an exposed floor (to outside air below)
and a semi-exposed floor (to an enclosed but unheated space
below) and the U-values in Table 20 are used."
Table 20 (excerpt, age bands A-G | H or I):
Age band Unknown/as built 50mm 100mm 150mm
A to G 1.20 0.50 0.30 0.22
H or I 0.51 0.50 0.30 0.22
Cert 000565 Summary §9 2nd Extension lodges:
Location: U Above unheated space
Type: N Suspended, not timber
Insulation: R Retro-fitted
Insulation Thickness: 200 mm
Default U-value: 0.22
Pre-slice the extractor's `_floor_details_from_lines` did NOT read
the "Insulation Thickness" cell (only the §8 roof extractor had the
field). FloorDetails carried no thickness → mapper plumbed
`SapBuildingPart.floor_insulation_thickness=None` → cascade
`u_exposed_floor(age=H, ins=None)` returned U=0.51 (Table 20 row[0]
unknown/as-built) vs worksheet 0.22 (Table 20 150 mm column for
age H) — over-counting BP[2] floor by (0.51-0.22) × 30 m² = +8.70
W/K.
Three-layer fix:
1. Schema (`elmhurst_site_notes.py:FloorDetails`) — add
`insulation_thickness_mm: Optional[int] = None` (mirror of
`RoofDetails`).
2. Extractor (`elmhurst_extractor.py:_floor_details_from_lines`) —
parse "Insulation Thickness" via existing `_local_val` (mirror of
`_roof_details_from_lines` pattern at line 333).
3. Mapper (`mapper.py:_map_elmhurst_building_part`) — translate
`floor.insulation_thickness_mm` to `SapBuildingPart.floor_
insulation_thickness=f"{n}mm"` (digit-prefix string convention
matching the API mapper + the wall pattern at line 3125-3129).
Cascade no-op: existing `_parse_thickness_mm` accepts "200mm" → 200;
`u_exposed_floor(age=H, ins=200)` returns 0.22 (clamps thickness ≥
125 mm to Table 20 row[3]) ✓.
Movement at HEAD (cert 000565):
- BP[2] Ext2 floor cascade U: 0.51 → 0.22 ✓ EXACT vs ws 0.22
- floor_w_per_k: 70.37 → 61.67 ✓ EXACT vs ws 61.67 (closed +8.70)
- sap_score (int): 28 → 29 ✓ EXACT vs ws 29
- sap_score_continuous: 28.31 → 28.5086 vs ws 28.5087 (Δ -0.20 →
-0.0001 — within 1e-4 strict floor!)
- SH: -38 kWh vs ws (was +218 → essentially closed)
Test count: 587 → 590 pass (+2 new AAA tests + sap_score integer
pin flipped from FAIL to PASS) + 8 expected 000565 fails (sap_score
integer pin removed from the work queue).
Cohort safety: only cert 000565 §9 lodges "Insulation Thickness"
(grep audit across Summary fixtures); cohort certs lodge "As built"
or omit the line. Pyright net-zero per touched file.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|---|---|---|
| .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