3614c14bf5
Closes the final `sap_windows: LEN 7 vs 3` divergence by replacing
the cohort 000477 hand-built's glazing-type-collapsed 3-window
encoding with 7 SapWindow entries mirroring the Summary §11 1:1 —
the same row breakdown the Elmhurst mapper extracts. Total area per
glazing-type group is preserved (cascade-equivalent):
g=0.72/U=2.0: 8.04 m² total — was 2 rows (E 1.28 + W 6.76),
now 6 rows (E 1.28 + W [1.8 + 1.7 + 1.36 + 1.36 + 0.54])
g=0.76/U=2.8: 1.17 m² in 1 row (unchanged)
Cohort 000477 is a single-bp dwelling, so every window's
`window_location` is "Main" — no per-bp apportionment complexity.
Cascade output unchanged: all 11 `_FIXTURE_PINS["000477"]` SapResult
pins remain GREEN at 1e-4 against worksheet `SAP value 65.0057`.
**Cohort 000477 is now fully Layer-2 GREEN** —
`test_from_elmhurst_site_notes_matches_hand_built_000477` passes with
zero load-bearing divergences between the mapped EpcPropertyData
(from `Summary_000477.pdf`) and the hand-built fixture.
Full sweep: 103 passed (was 102 pre-Slice-71; +1 new diff test),
10 failed (same 10 001479-related as documented in the handover).
Pyright net-zero on the touched fixture.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| docs | ||
| epr_data_exports | ||
| etl | ||
| infrastructure/terraform | ||
| model_data/requirements | ||
| packages | ||
| recommendations | ||
| scripts | ||
| services | ||
| sfr/principal_pitch | ||
| survey_report | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| AGENTS.md | ||
| 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_backlog.sh | ||
| 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