1928e5a2d6
Adds `SapRoomInRoofSurface` dataclass (kind + area + insulation thickness
+ insulation type) and an optional `detailed_surfaces` list on
`SapRoomInRoof`. When `detailed_surfaces` is present, the Simplified
A_RR formula is bypassed and the calculator iterates each surface,
applying the appropriate Table 17 / Table 4 U-value:
slope → roof_w_per_k via u_rr_slope (Table 17 col 1)
flat_ceiling → roof_w_per_k via u_rr_flat_ceiling (Table 17 col 2)
stud_wall → roof_w_per_k via u_rr_stud_wall (Table 17 col 3)
gable_wall → party_walls_w_per_k at U=0.25 (Table 4 "as
common wall")
This mapping mirrors the U985 worksheet for 000477 where RR stud walls
+ slope + flat-ceiling lines sit under (30) and RR gable walls sit
under (32). The §3.9 deduction of `A_RR_floor` from the storey-below
roof area still applies.
Synthetic test pins a 1-storey + RR dwelling with 4 detailed surfaces
(slope/stud_wall/flat_ceiling/gable_wall) at hand-computed U-values
from Table 17 and Table 4, abs=0.001 tolerance.
Reference: RdSAP 10 (10-06-2025) §3.10 page 24-25; Figure 4; Table 17
page 44; Table 4 page 22.
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