f68cea27c9
The Modelling glazing overlay's draught-proofing recompute (RdSAP 10 §8.1 — a count over openable windows + doors) needs every openable window captured with its draught_proofed flag. cert 001431's §11 lodges 17 windows but only 14 surfaced, via two distinct gaps: 1. Extractor (_extract_windows_from_layout): the one "Double glazing, known data" row whose §11 Data-Source cell is "BFRC data" was rejected — it is laid out as a standalone keyword line with the U-value on the next line and lodges no Frame Type/Factor/Gap cells, so it never matched the joined "<source> <U>" Manufacturer-line shape. Now anchored by a standalone data-source form, with the RdSAP 10 §3.7 default frame factor (0.7) for the absent frame cell. 2. Mapper (_is_elmhurst_roof_window): the two "Double pre 2002" rows (U 3.1 / 3.4 > 3.0) were reclassified as roof windows by the U-value backstop even though both are lodged on an "External wall". A window lodged on a wall is vertical by definition; guard the U-value backstop so it only fires when location/BP give no roof signal. The backstop's only pinned cert (000516 W6) hand-builds its sap_roof_windows and so is unaffected. With both closed: 17 sap_windows, 0 misrouted to sap_roof_windows, 14 draught-proofed — reconstructing Elmhurst's lodged 84% (16/19 = (14 windows + 2 doors) / (17 windows + 2 doors)). Full calculator + modelling + orchestration suites green (1885 pass); the 2 glazing draught-proofing xfails remain (the overlay recompute is the glazing agent's front). 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 | ||
| 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 | ||
| 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