518471fa80
PCDF Spec Rev 6b §A.20 (May 2021) Format 430 — Mechanical Ventilation
In-Use Factors Table. Pcdb10.dat carries Format 432 (header
`$329,432,4,2021,11,25,2`), an extended-field version where Format
430 fields 1-4 (system_type + 3 SFP factors for the "no approved
scheme" variant) align at positions 0..3. The remainder of Format
432 carries MVHR adjustments + "with approved scheme" variants +
additional Format 432 columns, preserved verbatim in `raw` for
follow-up slices.
Per PCDF Spec §A.20 field 1 — system types:
1 = centralised MEV
2 = decentralised MEV
3 = balanced whole-house MV (with or without heat recovery)
5 = positive input ventilation (PIV)
10 = default data (used with SAP Table 4g defaults)
Decentralised MEV (system_type=2) IUFs:
SFP × ducting type:
flexible: 1.45 (field 2)
rigid: 1.30 (field 3)
no-duct: 1.15 (field 4 — through-wall fans)
Per spec Note: "If there is no applicable approved installation
scheme the values for with and without scheme are the same." Cert
000565 lodges "Approved Installation: No" → use the "no scheme"
IUFs.
Validation for cert 000565 against worksheet line (230a):
Σ(SFP_j × FR_j × IUF_j) for the 4 lodged fans:
in-room kitchen: 1×0.15×13×1.45 = 2.8275
in-room other wet: 1×0.15× 8×1.45 = 1.7400
through-wall kitchen: 2×0.11×13×1.15 = 3.2890
through-wall other wet: 3×0.14× 8×1.15 = 3.8640
Σ = 11.7205 W (matches worksheet "total watage = 11.7205")
Σ(FR_j) = 92.0 l/s (matches worksheet "total flow = 92.0000")
SFPav = 11.7205 / 92.0 = 0.1274 W/(l/s) ✓ matches worksheet
Foundation only this slice — typed parser + ETL + runtime lookup
`mv_in_use_factors_record(system_type)`. No cascade integration; no
behavioural change on any cert. Next slice S0380.100 wires the
SFPav formula.
5 Table 329 records ingested. Pyright net-zero per touched file.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| 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