4eacfa6296
SAP 10.2 Appendix N3.5 Table N4 (PDF p.107) — heat-pump packages
with fixed daily heating durations:
- "24" → N24,9 = 365 (continuous): every day at heating temperature,
no off period → (days_in_month, 0) per month → MIT_zone = Th.
- "16" → N16,9 = 365 (unimodal, 0700-2300): every day with single
8h off → (0, days_in_month) per month → MIT_zone = Th − u1(8h).
- "9" → standard SAP schedule (bimodal 7+8 off): falls through to
`None` so the orchestrator applies the legacy bimodal path.
Cert 9418 (Daikin Altherma EDLQ05CAV3, PCDB 102421) lodges
`heating_duration_code = "24"` — worksheet (87) MIT_living = 21.0
every month (= Th1, no off period) and (90) MIT_elsewhere collapses
to Th2 directly. Pre-fix the bimodal cascade produced MIT ~17.8-19.8
(2.04°C low at Jan) and SAP was +2.20 over worksheet 84.6305.
Post-fix cert 9418 closes to SAP Δ +0.0296 (from +2.20) — the
residual is consistent with the same ~0.05 PSR-formula drift seen
in 5/7 cohort certs sharing PCDB 104568.
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