778b150c98
Extracts `water_heating_section_from_cert(epc) -> WaterHeatingResult`
helper to expose the full §4 cascade output for tests (mirrors the
existing private `_water_heating_worksheet_and_gains`, drops unused
args).
§4 pins at abs=1e-4:
scalar (2 line refs × 6 = 12): (42) occupancy, (43) annual avg L/day
monthly (7 line refs × 6 × 12 months = 504 assertions across 42
parametrized cases): (44)m daily, (45)m energy content,
(46)m distribution loss, (61)m combi loss, (62)m total demand,
(64)m output, (65)m heat gains
Per-fixture results:
000474: 9/9 PASS ✓
000477: 5/9 — combi loss (61)m diverges → cascades to
62/64/65 monthly
000480: 9/9 PASS ✓
000487: 1/9 — LINE_43 + every monthly fails (HW lodgement
defect: number_baths=1 but PDF arithmetic
suggests different shower/bath profile)
000490: 9/9 PASS ✓
000516: 9/9 PASS ✓
4/6 fixtures close §4 fully — strong cascade floor. The 000477 combi
loss residual is a specific Table 3c sub-row issue; the 000487 §4 gap
is part of its broader cert lodgement defect (RR + HW lodgement).
Cumulative scoreboard:
§1: 12 PASS / 0 FAIL
§2: 96 PASS / 0 FAIL
§3: 1 PASS / 23 FAIL (precision residuals + 000487 RR)
§4: 42 PASS / 12 FAIL
---
total: 151 PASS / 35 FAIL
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| docs | ||
| 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