412525ae6f
Two changes bundled (same file, same RdSAP 10 §15 spec citation):
1. Tighten cohort cert (000474 / 000490) heat_transmission LINE_xx
pins from abs=0.01 / 0.1 → abs=1e-4 (4 pins). Pre-slice the cohort
landed at 1e-4 of the U985 PDF but the test pins were holdovers
from when the cascade was less precise. Per [[feedback-e2e-
validation-philosophy]]:
"per-component tests pin against U985 worksheet line refs at
<1e-3 tolerance ... 1e-4 since PDF lodges 4 d.p."
Probe data at HEAD post-§15:
000474 LINE_33 cascade=209.108439 ws=209.1084 Δ=+4e-5
000474 LINE_37 cascade=232.116939 ws=232.1169 Δ=+4e-5
000490 LINE_33 cascade=211.893610 ws=211.8936 Δ=+1e-5
000490 LINE_37 cascade=236.621110 ws=236.6211 Δ=+1e-5
2. Update `test_room_in_roof_simplified_type_1` and `..._type_2`
expected-value formulas to round A_RR_shell to 2 d.p. per RdSAP
10 §15 (p.66) — matching the cascade behaviour now enforced by
Slice S0380.116. The unrounded expected was 100.9156 / 71.857;
spec-correct rounded is 100.919 (39.5285 → 39.53) and 71.846
(32.2749 → 32.27). Same abs=1e-4 pin enforces both arithmetic
and rounding correctness.
New import: `_round_half_up` from heat_transmission (the same
helper the cascade uses for §15 rounding).
Net pyright change: 71 → 71. Net test change: 4 newly-tight pins,
2 newly-passing RR synthetic tests, 670 → 670 passing.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|---|---|---|
| .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