d8cdee4e53
The Elmhurst Summary §14.2 Meters section lodges the electricity meter type as the bare RdSAP enum form "18 Hour", but `_METER_STR_TO_INT` only carried the legacy "off-peak 18 hour" alias. All 41 P960-format heating-system fixtures at `sap worksheets/heating systems examples/` lodge meter_type "18 Hour", so `cert_to_inputs` strict-raised on every one of them before this slice. Per RdSAP 10 Specification §17 page 85 (Electricity meter row 10-2): > "Electricity meter: Dual/single/10-hour/18-hour/24-hour/unknown" Per RdSAP 10 §12 page 62: > "if the meter is dual 18-hour/24-hour it is 18-hour/24-hour tariff" So the bare "18 Hour" lodging routes directly to enum 5 (Off-peak 18 hour) → `Tariff.EIGHTEEN_HOUR`, bypassing the §12 Rules 1-4 dispatch (which only fires for Dual meters that aren't 18-hour or 24-hour). After this slice the heating-system corpus probe (`/tmp/probe_*.py` across 41 variants of the same property × different heating systems) shifts from "32 raises + 7 mapper gaps + 2 emitter gaps" to "32 cascade-OK + 7 community-heating + 2 underfloor-emitter + 1 cylinder-size 'No Access'". The 32 newly-OK variants surface a positive ΔSAP cluster (cascade SAP_c > worksheet SAP_c by +0.87..+30 across boiler types) — that residual layer is queued for the next slice. Extended handover suite at HEAD post-slice: **829 pass, 0 fail** (baseline 775 + test_table_12a.py's 54 incl. the new "18 Hour" entry). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs/adr | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
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| 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