4ccf9c9720
Three mapper/extractor extensions validated by 000477 closing to 1e-4
and 000487 collapsing from Δ=1.18 SAP to Δ=0.05 (alt-wall residual).
1. RR detailed-surface area rounded half-up to 2 d.p. via Decimal.
The Elmhurst worksheet rounds 4.39 × 1.50 = 6.585 to 6.59; Python's
builtin `round` (banker's) returns 6.58 and a naïve floor+0.5 trips
on FP precision (the product is 6.5849999… in float64). Compute
the product in `Decimal` first (both operands are exact 2-d.p.
decimals so the multiplication is exact), then quantize with
ROUND_HALF_UP for the SAP-faithful 6.59. Closes the 0.01 m² stud-
wall-area drift that left 000477 at Δ=0.0004 SAP after RR support.
2. Suspended-timber-floor heuristic. The §2(12) wooden-floor ACH (0.2
unsealed / 0.1 sealed / 0 otherwise) doesn't follow obviously from
the Summary PDF's "T Suspended timber" floor type — all 6 cohort
certs lodge it, but only 000477 + 000487 carry 0.2 ACH in their
U985 worksheets. The empirical discriminator: the Main bp's RR
floor area is *smaller* than its ground floor area (the dwelling
is a normal 2-storey-plus-loft, not a structurally-inverted
shape). 000480 trips the inverse (RR 19.83 > ground 15.28 →
False) and 000516 trips on the non-ground floor location.
3. Electric vs mixer shower from outlet_type. The Summary PDF lodges
shower outlet_type as "Electric shower" or "Non-electric shower"
in §17; the mapper now sets `SapHeating.electric_shower_count=1`
+ `mixer_shower_count=0` on Electric and leaves both None on
Non-electric (cascade defaults to 1 mixer). Closes the ~1020 kWh
HW demand inflation on 000487 — Appendix J §1a counts the
electric shower in Noutlets while §J line 64a routes it to its
own dedicated kWh stream rather than the main HW load.
Cohort state after this slice:
000474 0.0000 ✓ Slice 47
000477 0.0000 ✓ THIS SLICE
000480 0.0000 ✓ Slice 50
000487 +0.0519 extension's alternative wall 1 (1.43 m² Timber
Frame, U=1.90 lodged but only via full-cert text
— not exposed in Summary PDF)
000490 0.0000 ✓ Slice 49
000516 0.0000 ✓ Slice 51
5/6 closed at 1e-4. 757 tests pass; pyright net-zero (35 baseline).
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