5e34594d8a
Wires PCDB main heating index + secondary heating type into the three open fixtures. All three certs lodge: - Vaillant ecoTEC PCDB index (000480=16839 pro 28, 000487=18119 sustain 28, 000516=18118 sustain 24) at main_heating_data_source=1. - Electricity Electric Panel/convector secondary (SAP code 691) at Table 11 fraction 0.10 (gas main + any secondary, page 188). - number_baths (000480=0, 000487=1, 000516=1). Confirmed against SAP 10.2 (14-03-2025) Table 11 page 188: "All gas, liquid and solid fuel systems" main + "all secondary systems" → fraction 0.10. PDF arithmetic on each fixture matches: 000480: 12398.58 × 0.10 = 1239.86 kWh secondary ✓ 000487: 10834.78 × 0.10 = 1083.48 kWh secondary ✓ 000516: 12410.32 × 0.10 = 1241.03 kWh secondary ✓ Impact on continuous SAP delta (target <0.01): fixture | pre S18a | post S18a | status --------|----------|-----------|--------- 000480 | +7.0885 | +0.0012 | ✓ within 0.01 000487 | +5.5285 | -1.9586 | over-corrected 000516 | +6.8375 | +0.0349 | nearly closed (0.04) 000480 hits the 0.01 continuous gate — first time outside 000490. 000516 is within 0.04 (was +6.84). 000487 swung from +5.5 to -2.0, suggesting the PCDB 18119 efficiency cascade diverges from what the PDF assumes for that specific boiler — separate slice. The previous fixture-lodgement gap was the dominant cost residual: (242) secondary cost was £0 and (240) main heating was over-counting because no PCDB efficiency was applied. Both close in this slice. The remaining (251) standing charges (£120) gap is a calculator-side issue addressed in the next slice (Table 12a page 191). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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| .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