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Verified against the SAP 10.2 spec (14-03-2025): Table 12 unit prices are IDENTICAL to SAP 10.3 Table 12. Both specs mandate (§12.2): "Fuel costs are calculated using the fuel prices given in Table 12. Other prices must not be used for calculation of SAP ratings." The legacy ML-pipeline prices in domain.ml.sap_efficiencies (3.48 gas, 13.19 elec, 5.50 E7-low) do NOT match either SAP 10.2 or 10.3 and appear to be a pre-2022 holdover. New module domain.sap.tables.table_12 carries the spec-correct values: mains gas: 3.64 (was 3.48 legacy) standard electricity: 16.49 (was 13.19) 7h-low / Economy-7: 9.40 (was 5.50) 24h-heating: 14.04 (was 6.61) Also corrects an S-B4 bug: SAP 10.2 Table 12a shows direct-acting electric heating (codes 191-196) runs at 90% high-rate on 7h tariffs, not 0% — only true storage heaters (401-409, 421-425) bill at the low rate. _E7_SPACE_HEATING_CODES narrowed accordingly. 100-cert parity probe with spec-correct prices: MAE 4.66 → 6.66 (regression vs legacy prices) bias -0.70 → -4.66 (over-counting cost) spec-correctness: SAP 10.2 verbatim The MAE regression confirms the corpus's lodged ratings were NOT calculated against the published SAP 10.2 Table 12 prices. The cert ratings appear to use the legacy lower prices despite reporting sap_version=10.2. Three paths forward documented in next commit's discussion thread. Also adds the SAP 10.2 spec PDF to docs/sap-spec/. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| docs | ||
| epr_data_exports | ||
| etl | ||
| infrastructure/terraform | ||
| model_data/requirements | ||
| packages | ||
| recommendations | ||
| scripts | ||
| services | ||
| sfr/principal_pitch | ||
| survey_report | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| AGENTS.md | ||
| 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_backlog.sh | ||
| 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