aa6645e3f1
Cert 0330 API path was at Δ +1.68 SAP after Slice 96 because all 11 windows (`sap_windows[*].glazing_type = 2`) fell through `_API_GLAZING_TYPE_TO_TRANSMISSION` (which only covered codes 3 + 13) to the cascade's `u_window` default (~U=2.5). The cert's actual glazing is "Double, England/Wales 2002 or later (before 2022)" per RdSAP 10 Table 24 page 79 → U=2.0, g=0.72 (PVC/wooden frame). RdSAP 10 Table 24 verbatim: Glazing Installed Gap U-value g Double or England/Wales: 2002 or later 2.0 0.72 triple Scotland: 2003 or later any glazed N. Ireland: 2006 or later The cascade's curtain-transform path (`U_eff = 1/(1/U + 0.04)`) takes U_raw=2.0 to U_eff=1.8519 — matching the worksheet's per- window (27) U value column to 4 d.p. across all 11 windows. Effect on cert 0330 API path: - Windows HLC 36.4545 → 29.7407 (= worksheet exact) - (37) total fabric heat loss 244.48 → 237.77 (≈ worksheet 237.75) - SAP Δ +1.68 → +2.12 (windows fix unmasks the standalone HW gap, which the next slice closes) Re-pinned residuals (5 affected golden certs): - 0240: PE +17.85 → +15.69; CO2 +1.01 → +0.90; SAP unchanged at -15 - 0300: PE +7.76 → +7.52; CO2 -0.25 → -0.27; SAP unchanged at +0 - 0390-2954: PE -26.46 → -28.68; CO2 -2.56 → -2.76; SAP unchanged - 7536: SAP +0 → +1; PE -3.45 → -6.51; CO2 -0.09 → -0.17 - 8135: PE -2.41 → -5.31; CO2 -0.02 → -0.07; SAP unchanged at +0 The PE/CO2 widening on some certs (vs lodged GOV.UK values) reflects the cascade now using the spec table U=2.0 where those certs may have lodged a higher project-specific U — the spec-table is the right floor for the API path; per-window measured U overrides would belong on the cert's window_transmission_details.u_value field, which the API JSON doesn't surface uniformly. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
||
|---|---|---|
| .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