6b934710d0
The RdSAP schema's `wall_insulation_type = 4` ("as-built / assumed")
covers two distinct cert populations that previously both routed to
the Cavity-as-built row (U=1.5 at band E):
686 certs: "Cavity wall, as built, no insulation (assumed)" — U=1.5 ✓
1171 certs: "Cavity wall, as built, insulated (assumed)" — should be 0.7
147 certs: "Cavity wall, as built, partial insulation (assumed)" — 0.7
The description string disambiguates. The legacy production map at
recommendations/rdsap_tables.py:753 routes the latter two to "Filled
cavity" — we match that interpretation here for parity with the cert
assessor and the production recommendation engine.
`_cavity_described_as_filled` adds the description check; the existing
filled-cavity dispatcher in u_wall now fires on either signal:
- wall_insulation_type == 2 (S-B23 — explicit filled-cavity code)
- description contains "insulated" or "partial insulation" without
the "no insulation" negation marker (S-B25 — assumed cavity-fill)
Parity probe at 300 certs, seed=7:
PE MAE 46.78 → 45.74 (-1.04)
PE bias 41.78 → 40.19 (-1.59)
Band F bias +23.2 → +12.6 (-10.6)
Band G bias +31.8 → +25.1 (-6.7)
Band H bias +30.7 → +15.5 (-15.2)
Improvements localise to bands F-H (1976-1995), the era when Building
Regs mandated cavity insulation for new-builds — making "as built,
insulated (assumed)" the modal description. SAP MAE drifted up
+0.12 (cost-side residuals surfacing now that envelope is closer to
spec; tracked for follow-up).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| docs | ||
| epr_data_exports | ||
| etl | ||
| infrastructure/terraform | ||
| model_data/requirements | ||
| packages | ||
| recommendations | ||
| scripts | ||
| services | ||
| sfr/principal_pitch | ||
| survey_report | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| AGENTS.md | ||
| 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_backlog.sh | ||
| 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