11a637c6bd
A hot-water cylinder lodging gov-API `cylinder_size=0` ("size not
determined", with has_hot_water_cylinder=true) resolved to a None volume
in `_cylinder_storage_loss_override` (which reads `_cylinder_volume_l_
from_code`, returning None for code 0). The subsequent `if volume_l is
None: return None` then DROPPED the cylinder's Table-2 storage loss
entirely — under-costing the DHW and over-rating the dwelling. Meanwhile
the Table-13 high-rate-fraction path already used `_hot_water_cylinder_
volume_l` (which defaults size 0 to 110 L), so the two DHW paths
disagreed on the same cylinder.
RdSAP 10 §10.5 Table 28 ("if the actual size is not determined, the size
is taken as according to Table 28") makes an unsized present cylinder the
110 L "Normal" baseline, which STILL incurs the storage loss. Fixed by
defaulting the storage-loss volume to 110 L for the explicit size-0 case.
Gated on the EXPLICIT 0 (not None): a full-SAP cert whose RdSAP
cylinder_size is simply unlodged (None, e.g. pinned 10091568921) keeps
its own cylinder handling rather than a forced 110 L RdSAP default.
7 corpus certs lodge cylinder_size=0 + has_cylinder=true. Gauge: within
77.0% -> 77.3%, SAP MAE ~flat (0.648), CO2 0.074 -> 0.073, PE 3.2 -> 3.05
(the previously-dropped storage loss now correctly counted in the demand
cascade). Unit-pinned in test_cert_to_inputs (storage loss non-None for
size 0); RealCertExpectation 200004017091 = 71.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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| .claude/skills | ||
| .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 | ||
| modelling_audit.md | ||
| next_claude_prompt.txt | ||
| P960-0001-001431-2.pdf | ||
| package-lock.json | ||
| package.json | ||
| playground.py.local-backup | ||
| pyproject.toml | ||
| pyrightconfig.json | ||
| pytest.ini | ||
| README.md | ||
| run_lambda_local.sh | ||
| serverless.yml | ||
| Summary_001431-3.pdf | ||
| 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