5402dd17e1
Per SAP 10.2 spec page 165 Table 4a Category 10 (Room heaters), the
600-range secondary-heating SAP codes split by fuel:
601-613: Gas (mains gas / LPG / biogas) — column A is mains gas.
621-625: Liquid fuel room heaters (oil / bioethanol).
631-634: Solid fuel room heaters (open fire, closed room heater
with/without boiler) — house coal is the modal default.
691-699: Electric room heaters.
`_elmhurst_secondary_fuel_from_sap_code` previously mapped the entire
601-630 range to mains gas (API code 26). Two bugs:
1. Codes 621-625 are oil heaters, not gas. (Cohort hasn't surfaced
an oil-secondary cert yet — deferred until a fixture exercises.)
2. Codes 631-634 are solid fuel, not gas, and weren't in the range
at all. Cascade fell through to the secondary-fuel-None default
(standard electricity at 13.19 p/kWh), over-charging cert 2102's
"Open fire in grate" secondary by ~£340/yr.
Narrow the gas range to 601-613 (per the spec) and add 631-634 → API
fuel code 11 (Coal in `_ELMHURST_MAIN_FUEL_TO_SAP10`) → Table 32
direct lookup returns 3.67 p/kWh (house coal), matching worksheet
(242) "Space heating - secondary 3585.2401 × 3.6700 = 131.58".
Cohort-2 outcome (38 certs, Summary path):
exact (<1e-4): 20 → **21** (+1: cert 2102 -15.81 → +5e-5)
±5+: 1 → **0** (last big-gap closed)
Cert 2102 verified end-to-end:
- secondary_heating_type=631 → secondary_fuel_type=11 → 3.67 p/kWh
- Cascade SAP 63.8732 vs worksheet 63.8732 (delta +5e-5)
- Cascade total fuel cost £787.03 = worksheet £787.03 exactly
Pyright net-zero on both touched files (mapper.py 32→32, test 0→0).
Tests: 703 → 704 pass (+1 new SAP-code-631 secondary-fuel routing
test), 10 expected fails unchanged.
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