9b0c590bf8
The flat floor-exposure heuristic keys on dwelling_type: a flat defaults to has_exposed_floor=False (assuming a heated dwelling below). The Elmhurst Summary path lodges a ground-floor flat's vertical position as a "Ground floor" floor_type rather than the API floor_heat_loss=1 exposed code, and the mapper can label such a flat "Top-floor flat" — so the cascade dropped the ground floor entirely (a ground floor is in contact with the ground and carries heat loss). Treat a "ground floor" floor_type as a heat-loss floor, overriding the dwelling-level suppression upward — mirroring the existing "another dwelling below" party override downward. Worksheet-validated to 1e-4 on simulated case 45 (a ground-floor flat the mapper labelled "Top-floor flat"): floor (28a) 0 -> 25.38 W/K, fabric (33) 75.63 -> 101.0104, HTC (39) 112.93 -> 145.3579, all matching the P960 exactly; SAP 67.81 -> 62.52. RdSAP-21.0.1 corpus within-0.5 69.5% -> 69.7% (MAE 0.859 -> 0.854). Floors ratcheted. Pinned in test_heat_transmission (ground-floor billed + party-floor suppressed). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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| .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