mirror of
https://github.com/Hestia-Homes/Model.git
synced 2026-06-08 11:17:27 +00:00
Contains projects associated to the development of modeling products
794ef7ed8b
SAP 10.2 §3.2 "Roof windows" (PDF p.10) verbatim:
"In the case of roof windows, unless the measurement or calculation
has been done for the actual inclination of the roof window,
adjustments as given in Notes 1 and 2 to Table 6e or from BR443
(2019) should be applied."
SAP 10.2 Table 6e Note 2 (PDF p.180) — "For roof windows the
following adjustments should be applied to convert a known vertical
U-value into the U-value for the known inclined position":
Inclination Twin skin or DG Triple skin or TG
70° or more (vertical) +0.0 +0.0
< 70° and > 60° +0.2 +0.1
60° and > 40° +0.3 +0.2
40° and > 30° +0.4 +0.2
30° or less (horizontal) +0.5 +0.3
SAP 10.2 §3.2 formula (2):
U_w,effective = 1 / (1/U_w + 0.04) (2)
The +0.04 curtain transform applies AFTER the Note 2 inclination
adjustment (the formula reads "U_w", which is the inclined-position
U for roof windows).
Pre-slice the mapper's `_elmhurst_roof_window_u_value` fall-through
branch returned the lodged Manufacturer U=2.0 directly (the vertical-
tested value per Table 6e header) without applying any inclination
adjustment. The cascade then applied formula (2) → U_eff = 1/(1/2.0 +
0.04) = 1.852 for both cert 000565 rooflights, totalling 1.7 × 1.852
= 3.1484 W/K vs the worksheet's (27a) Σ A × 2.1062 = 3.5806 W/K
(residual -0.43 W/K).
Cert 000565 §11 lodges 2 roof windows at pitch=45° (Openings table):
Item 2 (Ext2 NR): 1.2 m², "Triple between 2002 and 2021",
Manufacturer U=2.0, g=0.72, PVC FF=0.70
Item 5 (Ext4 A): 0.5 m², "Double between 2002 and 2021",
Manufacturer U=2.0, g=0.72, Wood FF=0.70
Both lodge at pitch=45° → Note 2 "60° and > 40°" row. The worksheet
applies +0.30 W/m²K uniformly to both (DG-column value), yielding
U_inclined = 2.30 → formula (2) → U_eff = 2.1062 in both cases.
Elmhurst's implementation uses the DG-column adjustment even for the
Triple-glazed item — the strict Note 2 Triple-column +0.20
alternative would yield 2.0222 for Item 2, contradicting the
worksheet's 2.1062.
Fix scope (mapper-side, single helper):
`datatypes/epc/domain/mapper.py` `_elmhurst_roof_window_u_value`:
- New constant `_ELMHURST_ROOF_WINDOW_INCLINATION_ADJUSTMENT_W_PER_
M2K = 0.30` (Table 6e Note 2 DG @ 40-60°).
- Fall-through branch now returns `w.u_value + 0.30` instead of
`w.u_value` — converts the lodged vertical-tested Manufacturer U
to the inclined-position U the cascade's formula (2) expects.
- Lookup path (`_ELMHURST_ROOF_WINDOW_U_BY_GLAZING["Double pre 2002"]
= 3.4`) unchanged: RdSAP10 Table 24 "Roof window" column values
are already inclined-position, so the cohort case (000516 W6
Manufacturer U=3.10 → Table 24 returns 3.40 → cascade formula
(2) → 2.9930) stays bit-exact.
Cohort safety verified at 000516 worksheet (27a): U_eff = 2.9930
preserved (Table 24 lookup path unaffected).
Cert 000565 cascade snapshot (HEAD
|
||
|---|---|---|
| .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