a8e5563ace
main_heating_category=9 (warm-air systems, NOT heat pump) had no entry in _SECONDARY_HEATING_FRACTION_BY_CATEGORY, so a warm-air main with a lodged secondary raised UnmappedSapCode in _secondary_heating_fraction_for_category — the last calc_raise in the API sample (cert 0380-2197-2590-2996-2715: warm air mains gas code 506 + electric room-heater secondary). SAP 10.2 Table 11 (p.188): a gas/oil warm-air unit falls under "All gas, liquid and solid fuel systems" (0.10), and electric warm air under "Other electric systems" (also 0.10) — so 0.10 regardless of fuel. The warm-air efficiency (Table 4a code→eff: 506→0.70) and Table 4f fan energy were already wired; this was the only missing dispatch entry. 0380 now computes: SAP 78.1 vs lodged 77 (+1.1; the residual is per-cert fabric/PV, not the warm-air dispatch — a faithful 0380 worksheet isn't available, sim case 28 diverges at SAP 57 / code 502 / condensing unit). Eval: zero raises remain, computed 908→909; mean|err| 1.703→1.702. Regression green (2448 pass incl. golden 6035 + cohort); pyright net-zero (44=44). 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 | ||
| 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 | ||
| 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