94275d07cc
RdSAP 10 §10.5 (PDF p.55): "If the actual size is not determined, the size of a hot-water cylinder is taken as according to Table 28." When a cylinder is present (has_hot_water_cylinder) but no size descriptor resolves — the gov API lodges cylinder_size=0, or Exact with no measured volume — `_hot_water_ cylinder_volume_l` returned None, silently dropping BOTH the cylinder's storage loss and the Table 13 electric-DHW high-rate fraction, under-costing and over-rating the dwelling. Default such cylinders to the Table 28 baseline "Normal" 110 L (the value §10.7 also instantiates as the first-row default). The context-dependent Inaccessible 210/160 values are deliberately NOT applied here — they are tied to the explicit "Inaccessible" descriptor (code 5) the assessor lodges, not to an unpopulated size field. Scope: 7 of 301 cylinder certs in the corpus (2%). Correctness fix — closes a real spec gap; marginal on the headline (within-0.5 66.1% unchanged, MAE 1.128 -> 1.124) because these certs' residual is dominated by a separate HW- demand gap, not the cylinder. Worksheet harness 47/47 0 diverge (Summary certs lodge a real size, so the fallback never fires). 1 AAA test, pyright net-zero. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| .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 | ||
| 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