c496f345f8
Three changes surfaced by the 25k 2026 run: - transform._peui_ucl returns None for non-positive raw PEUI (net-exporters). apply_ucl_correction would otherwise raise ValueError on negative input. - PhotovoltaicArray scalars (peak_power, pitch, orientation, overshading) now accept Measurement | int | float in the schema; mapper coerces via _measurement_value. - train_baseline reports sMAPE alongside MAPE — handles zero-actual rows (e.g. co2_emissions for net-zero certs) where MAPE explodes. Results at N=25,000 RdSAP 2026 certs (~32s end-to-end): sap_score MAPE=0.064 sMAPE=0.054 R^2=0.762 co2_emissions sMAPE=0.140 R^2=0.890 peui_raw MAPE=0.126 sMAPE=0.120 R^2=0.714 peui_ucl MAPE=0.114 sMAPE=0.108 R^2=0.736 space_heating_kwh MAPE=0.167 sMAPE=0.157 R^2=0.915 hot_water_kwh MAPE=0.089 sMAPE=0.086 R^2=0.737 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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| .github/workflows | ||
| .idea | ||
| .vscode | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| docs/adr | ||
| 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