0fae84d2b6
Completes `_elmhurst_secondary_fuel_from_sap_code` per SAP 10.2 §12 (PDF p.34: "Secondary heating systems and applicable fuel types are taken from the room heaters section of Table 4a") + RdSAP 10 §10.4.1. Each Table 4a room-heater code now resolves to its fuel CATEGORY's modal fuel: - gas room heaters 601-613 → mains gas (26 → Table 32 1, 3.48 p/kWh) - liquid room heaters 621-625 → heating oil (28 → Table 32 4, 5.44 p/kWh) - solid room heaters 631-636 → house coal (11 → Table 32 11, 3.67 p/kWh) - electric room htrs 691-694/699/701 → None (cascade electricity default) Previously only the gas (601-613→26) and solid (631-634→11) blocks were mapped; liquid heaters (621-625) and 635-636 fell through to None → silently billed as electricity (13.19 p/kWh), a large mis-price for an oil/solid heater. The prior slice raised on those; this maps them to the correct category fuel instead, and keeps the raise ONLY for codes inside the room-heater range (601-701) that are not a recognised Table 4a row. The specific sub-fuel within a category (mains gas vs LPG vs biogas) is a SEPARATE lodgement per §10.4.1 and is NOT exported in the Summary, so the gas block stays the modal mains gas — worksheet "simulated case 37" lodged its 605 live-effect fire on biogas (7.60 p/kWh), unrecoverable from the Summary code alone (this is the entire +7 SAP case-37 gap: secondary energy £131 + a separate biogas standing charge £70; every other line matches the worksheet exactly, incl. (206) main efficiency 61%). 5 AAA tests, harness 47/47 (0 raised), pyright net-zero, regression clean, corpus gauge unchanged (Elmhurst-path only). Co-Authored-By: Claude Opus 4.8 <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 | ||
| harness | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| sap worksheets | ||
| 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 | ||
| next_claude_prompt.txt | ||
| 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