5c11fd35c8
Reduced-field window U: heat_transmission derived the synthesised-window raw U from u_window(all None) -> the 2.5 placeholder regardless of glazing. Now routes the (uniform) glazing_type code through u_window (RdSAP Table 24) so e.g. double pre-2002 reads 2.8, not 2.5. Only the pre-SAP10 reduced-field path is affected (21.0.1 certs carry per-window U upstream) — the RdSAP-21.0.1 corpus gauge is unchanged at 66.9% within-0.5. test_real_cert_sap_accuracy: pin uprn_10002468137 (RdSAP-17.1, all-electric storage heaters) at SAP 61, validated against Elmhurst on identical inputs (dual off-peak immersion, 110 L cylinder, 2 baths). Our engine reproduces Elmhurst's fuel cost to the penny; lodged 55 is the old SAP-2012 schema. Tooling to grow the accuracy corpus: - scripts/fetch_real_life_epc_sample.py — capture a cert by UPRN into the corpus. - scripts/compare_epc_paths.py — diff gov-API vs Elmhurst-summary EpcPropertyData and run both through the engine, localising mapper vs calculator differences. - skill validate-cert-sap-accuracy — the end-to-end loop (capture -> Elmhurst inputs -> human builds -> compare -> reconcile -> pin in the test). - skill epc-to-elmhurst-rdsap-inputs reference: corrected immersion (code 1=dual), cylinder size (code 2 = Normal/110 L), and bath-count (WWHRS sub-tab) mappings. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| .claude/skills | ||
| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| harness | ||
| 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 | ||
| next_claude_prompt.txt | ||
| 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