65cb094abe
Make the leave-one-out runner ADR-0030-compliant: - Hold out only SAP 10.2 targets (sap_version == 10.2) — the source cohort keeps every vintage (components are methodology-agnostic). - Label Component Accuracy as the PRIMARY, calculator-independent section. - End-to-end vs API-lodged (SECONDARY, calculator-FLOORED): add CO2 (tonnes) and PEI (kWh/m2) alongside SAP, using the canonical performance.py mapping (co2_kg/1000; primary_energy_kwh_per_m2). - Add the attribution readout calc(actual) vs lodged SAP — the calculator floor the end-to-end can reach. - Drop the neighbour-mean-of-lodged-SAP baseline (mixes SAP versions — rejected by ADR-0030). On the 181 SAP-10.2 targets: component rates are higher than the all-vintage view (age band 60.9 -> 78.5%, floor_area mean|.| 12.7 -> 8.4). End-to-end SAP MAE 6.34 vs the calc(actual) floor of 3.25 — ~half the gap is the known API-path calculator residual, not prediction error. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| harness | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
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| survey_report | ||
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| utils | ||
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| ara_backend_design.md | ||
| BaseUtility.py | ||
| CLAUDE.md | ||
| conftest.py | ||
| CONTEXT.md | ||
| devcontainer.sh | ||
| Dockerfile.test | ||
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| Makefile | ||
| MEMORY.md | ||
| next_claude_prompt.txt | ||
| package-lock.json | ||
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| pyrightconfig.json | ||
| pytest.ini | ||
| README.md | ||
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| test.requirements.txt | ||
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| 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