c28b061cfb
Elmhurst Summary §14.0 Main Heating1 leaves "Fuel Type" empty for
Table 4b liquid-fuel boilers (heating oil / HVO / FAME / B30K /
bioethanol — SAP codes 120-141). Unlike gas boilers (codes 101-119)
where Elmhurst explicitly lodges "Mains gas", liquid-fuel boilers
take the fuel from §15.0 "Water Heating Fuel Type" since the same
boiler heats space + water.
Pre-slice:
- `_elmhurst_main_fuel_int(mh.fuel_type)` returned None for the
empty §14.0 fuel string.
- The electric-SAP-code inference (`_ELECTRIC_SAP_MAIN_HEATING_CODES`)
didn't fire because SAP 127 is a Table 4b oil boiler, not electric.
- `main_fuel_type` fell through to the raw empty string.
- `cert_to_inputs._main_fuel_code` returned None.
- `table_32.unit_price_p_per_kwh(None)` defaulted to mains gas
(3.48 p/kWh).
- The cascade therefore priced ~13.7k kWh/yr of oil space + water
heating at the gas tariff — a 56% under-count vs the worksheet's
Table 32 oil rate.
Two complementary fixes:
1. Add "Heating oil" → 28 ("oil (not community)" per epc_codes.csv
row main_fuel,28) to `_ELMHURST_MAIN_FUEL_TO_SAP10`. The existing
`API_FUEL_TO_TABLE_32` then routes API 28 → Table 32 code 4
(heating oil — 7.64 p/kWh / 0.298 kg CO2/kWh / 1.180 PE factor
per RdSAP 10 spec p.95). This fix handles pcdb 1 directly because
pcdb 1 lodges §14.0 "Fuel Type: Heating oil" explicitly.
2. Thread a §15.0-fuel fallback for the main_fuel inference: when
`mh.fuel_type` is empty AND `mh.main_heating_sap_code` is in the
Table 4b liquid-fuel range (120-141 per SAP 10.2 Table 4b
"Seasonal efficiency for gas and liquid fuel boilers"), use the
§15.0 water_heating_fuel as the main fuel too. Gated on the SAP
code range so this can't accidentally fire on solid-fuel-mains
+ electric-HW certs (where §15.0 lodges "Electricity" for the
immersion but the SH fuel is the solid fuel implicit in the SAP
code). This fix handles oil 1 + oil pcdb 1/2/3 (where §14.0 is
silent but §15.0 lodges "Heating oil").
Residual shifts at HEAD post-slice (5 variants legitimately re-pinned):
oil 1 +13.67 SAP → -9.70 SAP (cascade now over-counts at the
spec's 7.64 p/kWh — vs worksheet's 5.44)
oil pcdb 1/2 +11.17 → -11.63
oil pcdb 3 +11.87 → -10.87
pcdb 1 +21.90 → -9.41
Remaining negative residuals are the price-spec-vs-worksheet gap
queued for slice S0380.131 (5.44 vs 7.64 p/kWh oil). The mapper now
correctly identifies the fuel; what's left is the cascade tariff.
The other 36 corpus variants are unchanged — restricting the §15.0
fallback to SAP 120-141 keeps solid-fuel-mains and electric-mains
certs at their existing pins.
Extended handover suite at HEAD post-slice: **874 pass, 0 fail**
(was 873 + 1 new AAA test).
Pyright net-zero on touched files (45 → 45 — pre-existing errors
unrelated).
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