3f68ec1f0d
SAP 10.2 Table 4f (PDF p.174) "Electricity for fans, pumps and other
auxiliary uses" row:
Liquid fuel boiler — flue fan and fuel pump 100 kWh/yr c) d)
Note c): "Applies to all liquid fuel boilers that provide main heating,
but not if boiler provides hot water only. Where there are two main
heating systems include two figures from this table."
Pre-slice the cascade's `_table_4f_additive_components` only wired:
- (230a) MEV / MVHR
- (230e) Main 2 gas-boiler flue fan (45 kWh)
- (230g) Solar HW pump
The liquid-fuel sibling row was missing — oil 1 worksheet (230d) and
oil pcdb 3 worksheet (230d) both lodge 100 kWh/yr "oil boiler pump"
that the cascade was silently skipping.
Implementation:
- Add `_LIQUID_FUEL_CODES = frozenset({4, 71, 73, 75, 76})` and new
`is_liquid_fuel_code(fuel_code)` helper in
`domain/sap10_calculator/tables/table_32.py`. Mirror of
`is_electric_fuel_code` — routes through `_to_table_32_code`
normalisation so Elmhurst-derived Table 32 codes (e.g. code 23
= bulk wood pellets, solid) don't collide with API enum codes
(where 23 = B30D community).
- Extend `_table_4f_additive_components` to add 100 kWh for Main 1
when `is_liquid_fuel_code(main.main_fuel_type)` returns True
(`isinstance(int)` guard for the `Union[int, str]` field). Mirror
the same gate for Main 2 per Note c) "Where there are two main
heating systems include two figures".
- LPG is GAS (Table 4b/4f convention, Ecodesign classification) —
`_LIQUID_FUEL_CODES` deliberately excludes 2/3/5/9 LPG codes.
Cascade impact across heating-systems corpus:
| Variant | SAP Δ | Cost Δ | PE Δ |
|-----------|-------------|-------------|-------------|
| oil 1 | +1.18→+0.60 | -£27→-£14 | -276→-124 |
| oil pcdb 1| +0.42→-0.15 | -£10→+£3.4 | -84→+67 |
| oil pcdb 2| +0.42→-0.15 | -£10→+£3.4 | -84→+67 |
| oil pcdb 3| +1.16→+0.59 | -£27→-£14 | -271→-120 |
| pcdb 1 | +0.57→-0.03 | -£13→+£0.6 | -109→+42 |
Cohort closures: pcdb 1 EXACT (-0.03), oil pcdb 1/2 closed to -0.15.
Golden fixtures impact:
- cert 0240 (dual-main oil combi 130): SAP integer 73→72 (resid
+0→-1), PE +1.02→+2.52, CO2 +0.11→+0.14. Dual-main certs add
2 × 100 = 200 kWh aux per Note c). Cert's published SAP 73
suggests the dual-main Q_space split (main_heating_fraction)
may also need wiring — slice candidate.
- cert 0390 (Firebird PCDF 9005 oil combi): PE -28.50→-28.08
(CLOSER to zero), CO2 -2.75→-2.73 (CLOSER to zero), SAP +7
unchanged.
Test:
test_sap_table_4f_liquid_fuel_boiler_flue_fan_and_fuel_pump_adds_
100_kwh — asserts oil pcdb 3 inputs.pumps_fans_kwh_per_yr ≥ 230
(130 base + 100 liquid fuel boiler aux).
Extended handover suite: 891 pass, 0 fail. Pyright net-zero (44=44).
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