61c215bf1f
RdSAP10 §15 p.66 (Rounding of data):
"All internal floor areas and living area: 2 d.p."
Cert 2536 (3 habitable rooms → Table 27 fraction 0.30,
TFA 45.65 m^2) sits ON the HALF_UP rounding boundary:
0.30 (exact) * 45.65 = 13.6950
HALF_UP 2 d.p. = 13.70
(worksheet fLA = 13.70 / 45.65 = 0.3001)
Float arithmetic drops the spec product BELOW the boundary:
0.30 (binary) ~= 0.2999999...
product ~= 13.69499...
HALF_UP 2 d.p. = 13.69
(cascade fLA = 13.69 / 45.65 = 0.29989)
The 0.00021 fLA shortfall feeds straight into the worksheet
(91) -> (92) MIT blend, undershoots MIT by ~0.001 C, and
shaves 0.29 kWh off (98c) useful space heating — a +0.0007
SAP residual via the (211) main heating fuel x p/kWh.
Compute the product in Decimal so HALF_UP lands on the exact
.005 decimal boundary the spec defines. Certs that sit off the
boundary (e.g. 2800/4800: 0.30 x 46.87 = 14.0610 -> 14.06 in
both Decimal and float) are unaffected.
Cohort-2 distribution after S0380.31..S0380.34:
36 exact + 2 <=0.07 (was 35 exact + 3 <=0.07).
Cert 2536: +0.000715 -> -9.2e-8.
The remaining 2800 / 4800 +0.0007 residuals come from a
different cause (off the HALF_UP boundary) — defer to a
separate slice.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs/adr | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| 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 | ||
| 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