999eced9fb
Cert 0240's SAP residual (-1) and a chunk of its PE/CO2 was an API-mapper
bug: it flattened ALL windows into sap_windows, so the 6 windows lodged
with window_wall_type=4 — the RdSAP code for a roof window ("Roof of Room"
rooflight / inclined glazing) — were billed as vertical wall glazing on
worksheet (27) at U=2.0, instead of roof windows on (27a) at the Table 6e
Note 2 inclination-adjusted U (DG 2002+ vertical 2.0 + 0.30 = 2.30) with
45°-inclined solar gains.
window_wall_type=4 is the discriminator, NOT window_type=2 (certs 0390 /
7536 lodge window_type=2 on ordinary main-wall windows). Fix: partition
the 21.0.1 API window list into sap_windows (wall_type≠4) + sap_roof_
windows (wall_type=4); `_api_sap_roof_window` mirrors the site-notes
`_map_elmhurst_roof_window` (vertical U from the glazing Table-24 lookup +
0.30 inclination; 45° pitch; g/FF from the same lookup).
Validated against the simulated-case-6 worksheet, which bills these
identical windows on (27a) at U_eff 2.1062 (= 2.30 with the §3.2 R=0.04
curtain transform). The inclined solar gain dominates the higher U-loss,
RAISING the SAP:
- 0240: SAP cont 72.14 → 72.55 (resid -1 → +0 EXACT), PE +3.91 → +1.95,
CO2 +0.22 → +0.12
- 6035: 2 wall_type=4 rooflights — SAP still +0 exact, PE +1.84 → +1.37,
CO2 +0.01 → -0.0004
Blast radius is exactly these two certs (only golden fixtures with
wall_type=4). Suite: 2354 passed, 1 skipped. New code: 0 pyright errors.
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 | ||
| 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 | ||
| 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