8443c77069
Closes the cert 0330 API path Layer 4 gate (Δ -0.000011 vs worksheet
SAP 61.5993) by surfacing two previously-broken inputs to the HW
cascade plus aligning the wall-net-deduction with the worksheet's
2-d.p.-per-window rounding convention.
(a) RdSAP schema 21.0.x `shower_outlets` shape mismatch:
real-API certs lodge `[{"shower_outlet_type": N, "shower_wwhrs":
M}, ...]` (a list of bare ShowerOutlet dicts), but the schema
modelled it as `[ShowerOutlets]` with nested
`{"shower_outlet": {...}}` wrappers. `from_dict` silently dropped
every bare element's payload (left `shower_outlet=None`),
blanking the cascade's mixer/electric counts on cert 0330 (and 4
other golden fixtures). Normalisation in `from_api_response`
rewrites the bare list shape to the wrapped form before
`from_dict` parses, so the schema's `ShowerOutlets` dataclass
sees the data it expects — no schema-class breakage downstream.
New helper `_count_shower_outlets_by_type` walks the normalised
list and counts outlets by integer code:
- code 1 → mixer (drives `mixer_shower_count`)
- code 2 → electric (drives `electric_shower_count`)
Empirically derived from the golden cohort + Summary mapper
cross-check (cert 0330 lodges code 2 + Summary surfaces "Electric
shower"; cert 0240 lodges multiple code-1 outlets on a
conventional oil-boiler + cylinder dwelling). No spec page
reference found.
Wired into both `from_rdsap_schema_21_0_0` and
`from_rdsap_schema_21_0_1`. Effect on cert 0330 API path:
`mixer_shower_count` 1 (cascade default) → 0; `electric_shower_
count` None (= 0) → 1; HW kWh 3172.65 → 2111.93. SAP Δ +2.1155
→ -0.0012.
(b) Per-window 2-d.p. area rounding in wall-net deduction:
RdSAP 10 §15 rounds per-window area at 2 d.p. before any sum.
The cascade's `windows_w_per_k_total` branch already rounds
per-window for the curtain transform; the wall-net deduction
branch (computing `gross_wall - windows - door` for the (29a)
line) was rounding the SUM once, which for cert 0330's 9 Main
windows yields 12.22 m² vs the worksheet's per-window-rounded
12.23 m² — Δ +0.01 m² × U=1.5 = +0.015 W/K on (29a). Aligned
both branches to round per-window, matching worksheet line (27).
SAP Δ -0.0012 → -0.000011.
Layer 4 chain test added:
- `test_api_0330_full_chain_sap_matches_worksheet_pdf_exactly` pins
cert 0330 API path SAP at 1e-4 vs worksheet 61.5993. This is the
second boiler validation cert with a Layer 4 1e-4 gate (cert
001479 is the first).
Re-pinned golden cert residuals (shifted by changes (a) and (b)):
- 0300: PE +7.52 → +8.44, CO2 -0.27 → -0.23 (Slice 98a — electric
shower count surfaced; cert has 1 electric + 1 mixer outlets)
- 2130: PE -38.17 → -38.18, CO2 +0.305 → +0.304 (Slice 98b —
window rounding edge)
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