960419a901
Lodges the missing cert fields on 000477 build_epc to match U985 PDF: - sap_windows = SECTION_6_VERTICAL_WINDOWS (was empty) - low_energy_fixed_lighting_bulbs_count = 9 (was None) - sap_heating.main_heating_details with PCDF index 18118 (was default) - sap_heating.secondary_heating_type = 691 (was None) - sap_heating.number_baths = 0 (PDF lodges 0 baths; was None → defaulted to "has bath"=True) `make_sap_heating` accepts a new `number_baths` kwarg to surface that field — it lives on SapHeating but wasn't exposed before. Impact: 000477 SAP integer 71 → 66 (PDF 65, Δ +6 → +1); cost £599 → £707 vs PDF £732 (Δ -22% → -3.5%); useful 9059 → 10067 vs PDF 10111 (matches to <0.5%). Remaining +1 SAP integer delta is the **Table 3c two-profile combi- loss override** — not yet implemented. PCDB 18118 (Vaillant ecoTEC sustain 24) lodges separate_dhw_tests=2 → spec Appendix J §J3 uses both Profile M (F1, R1) and Profile L (F2, R2) loss factors. Our override gate (`_pcdb_table_3b_combi_loss_override`) only accepts separate_dhw_tests==1 → falls back to Table 3a keep-hot time-clock 600 kWh/yr default = 25x overshoot vs the fixture-pinned ~24 kWh/yr. The same gap blocks 000480 (PCDB 16839 — but actually wait, 16839 is in 000490 too and that already closes — needs checking), 000487 (PCDB 18119), and 000516 (PCDB 18118). Test pin `test_elmhurst_000477_end_to_end_sap_score_matches_pdf` xfail (strict) with rationale pointing at Table 3c. Re-enables when the override implements. 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