e25aa02109
Elmhurst Summary §14.0 Main Heating1 sometimes lodges the bare form
"Heat Emitter: Underfloor Heating" without a subtype qualifier (in
screed / timber floor). The mapper's `_ELMHURST_HEAT_EMITTER_TO_SAP10`
dict only carried the qualified forms, so the bare lodging fell through
to None and was passed as a raw string into `MainHeatingDetail.heat_
emitter_type` — causing `_responsiveness` to strict-raise
`UnmappedSapCode` on every cert with this lodging (2 variants on the
heating-systems corpus: `electric 1` + `oil 6`).
Per RdSAP 10 Specification §10.11 Table 29 page 56 ("Heating and hot
water parameters"):
> "Underfloor heating: If dwelling has a ground floor, then according
> to the floor construction (see Table 19 if unknown):
> - solid, main property age band A to E: concrete slab
> - solid, main property age band F to M: in screed
> - suspended timber: in timber floor
> - suspended, not timber: in screed
> Otherwise (i.e. upper floor flats), take floor as suspended"
New helper `_resolve_elmhurst_underfloor_subtype` keys off the main BP's
`floor.floor_type` + `construction_age_band` and returns:
- SAP10.2 Table 4d emitter code 2 (in screed) → R=0.75 — for
solid + age F-M, suspended-not-timber, and upper-floor-flat cases
- SAP10.2 Table 4d emitter code 3 (timber floor) → R=1.0 — for
suspended-timber
The solid + age A-E "concrete slab" branch (R=0.25) has no cert-side
enum entry yet, so the helper strict-raises `UnmappedElmhurstLabel`
when that combination lands — the next variant lodging an A-E solid
underfloor will surface the gap loudly per
[[reference-unmapped-sap-code]].
Property 001431 (the heating-systems corpus dwelling) lodges §9.0
"Type: S Solid" + §3.0 "Date Built: G 1983-1990" (age band G ∈ F-M)
→ "in screed" → code 2 → R=0.75. Both `electric 1` and `oil 6` now
cascade-execute (corpus tally 32 → 34 OK / 41 populated).
Extended handover suite at HEAD post-slice: **830 pass, 0 fail**
(was 829 + 1 new AAA test).
Pyright net-zero on touched files (45 → 45 — pre-existing errors
unrelated).
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