02092c8041
SAP 10.2 Table 3 (PDF p.160) verbatim:
Primary loss is set to zero for the following:
Electric immersion heater
Combi boiler ...
CPSU ...
Boiler and thermal store within a single casing
Separate boiler and thermal store connected by no more than 1.5
m of insulated pipework
Direct-acting electric boiler
Heat pump (...) with hot water vessel integral to package
The Elmhurst WHC=903 lodging signals exactly the first row: "HW from
a separate electric immersion heater" — the cylinder is heated by an
immersion element inside the tank, no primary pipework between any
heat generator and the cylinder. The rule is universal: regardless
of what main heating exists for space heating, electric immersion
means no primary circuit means no primary loss.
Pre-slice `_primary_loss_applies` only consulted `water_heating_code`
in the Table 4a wet-boiler branch (codes 151-161 / 191-196). The Cat
4 HP branch returned True unconditionally when no PCDB record was
lodged; the Cat 1/2 boiler branch returned True unconditionally; the
PCDB Table 322 + Table 4b non-PCDB branches likewise. For the
electric 2 corpus variant (sap_main_heating_code=524 Cat 5 warm-air
ASHP, main_heating_category=4 per Elmhurst mapper, no PCDB record,
WHC=903 + cylinder), the Cat-4 branch falsely returned True and the
cascade added ~510 kWh/yr primary loss to a system with no primary
circuit at all.
Per-line walk discipline applied: cascade `water_heating_from_cert`
output dump showed `primary_loss_monthly_kwh_annual = 509.98` while
worksheet (59)m = 0 every month → spec lookup found Table 3 verbatim
"Electric immersion heater" zero-loss line.
Adds `_WHC_ELECTRIC_IMMERSION: Final[int] = 903` constant + a
top-of-function `if water_heating_code == _WHC_ELECTRIC_IMMERSION:
return False` guard that fires before any of the system-type-keyed
branches.
Closures electric 2:
HW kWh 2849.22 → 2339.24 (matches worksheet (62)/(64) = 2384.12
within the residual ~45 kWh storage-loss gap)
ΔSAP −0.4584 → +0.8118 (cascade swung past the worksheet by +1.27
— the pre-slice 'near-correct' value was offsetting cascade bugs
per [[feedback-software-no-special-handling]]; the +0.81 residual
exposes a separate upstream gap to chase in a follow-up slice)
Δcost +£10.56 → −£18.71
ΔCO2 +47.89 → −7.21 kg
ΔPE +443.13 → −161.68 kWh
No regressions on the other 24 cohort variants — only electric 2 has
the (Cat 4 HP, no PCDB, WHC=903) combination in the corpus.
Extended handover suite: 900 pass / 0 fail (was 899 — +1 from the
new AAA test). Pyright net-zero (43 → 43).
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 | ||
| 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