482ce88b55
SAP 10.2 Table 5a (PDF p.177) row "Warm air heating system fans
a) c)" computes the gain as SFP × 0.04 × V (W). Footnote c) sets
the default SFP to 1.5 W/(l/s) when no PCDB warm-air-unit record
is lodged; footnote a) applies the heating-season-only mask
(zero in summer months). Footnote c) further omits the gain when
the dwelling has balanced whole-house mechanical ventilation
(MVHR / MV) — same omission as the Table 4f kWh-side footnote e).
Pre-slice the cascade's `internal_gains_from_cert` only wired the
central-heating-pump row of Table 5a; the warm-air-fan gain helper
(`warm_air_heating_fan_w`) existed but was unwired. The kWh-side
parallel (Table 4f, 136.35 kWh/yr) was wired in S0380.158 — this
slice closes the symmetry on the gain side.
Per-line walk on electric 2 (SAP code 524 = Cat 5 ASHP with
warm-air distribution, V = 227.25 m³, no balanced MV):
worksheet (70)[Jan] = 13.6350 W
cascade (70)[Jan] = 0.0000 W delta = -13.635 W
worksheet (98c)[Jan] = 1600.43 kWh
cascade (98c)[Jan] = 1608.12 kWh delta = +7.69 kWh
13.635 W = 1.5 × 0.04 × 227.25 exactly. The -13.6 W winter gain
shortfall propagates through the §7 utilisation cascade and over-
states cascade SH demand by ~57 kWh/yr (cascade 9483 vs worksheet
9426), under-charging cost by ~£2.50 with opposite sign to the
S0380.156-.158 closures.
Fix: new `_any_main_system_has_warm_air_distribution(epc)` +
`_has_balanced_mechanical_ventilation(epc)` predicates in
`internal_gains.py`, mirroring `cert_to_inputs._TABLE_4A_WARM_AIR_SAP_CODES`
+ `_BALANCED_MV_KIND_NAMES` (kept here as siblings so the worksheet
layer stays free of rdsap deps). Orchestrator wires
`warm_air_heating_fan_w(sfp=1.5, dwelling_volume_m3)` into the
heating-season term of `pumps_fans_monthly_w` when warm-air
distribution is present and balanced MV is not.
Closures electric 2:
ΔSAP_c -0.1087 → -0.0000 EXACT
Δcost +£2.50 → -£0.00 EXACT
ΔCO2 +16.54 → +11.95 (joins lighting-PE deferred cohort)
ΔPE +97.69 → +48.66 (joins lighting-PE deferred cohort)
Electric 2 joins the 15-variant lighting-PE deferred cohort
(electric 1 + electric 3/5/6/7/8/9 + solid fuel 5/6/7/8 + solid
fuel 4/9/10/11 + electric 2) where SAP/cost are EXACT but PE/CO2
carry an Elmhurst-vs-spec MONTHLY-factor offset (cohort uses
Table 12 annual factors on the off-peak HW immersion line; spec
mandates Table 12d/12e monthly per the header).
Verbatim spec quote (SAP 10.2 Table 5a row "Warm air heating
system fans a) c)", PDF p.177):
"Warm air heating system fans a) c) SFP × 0.04 × V"
Footnote c): "SFP is the specific fan power from the database
record for the warm air unit if applicable; otherwise
1.5 W/(l/s). These values of SFP include an in-use factor.
If the heating system is a warm air unit and there is balanced
whole house mechanical ventilation, the gains for the warm air
system should not be included."
Footnote a): "... Set to zero in summer months. ..."
Σ |ΔSAP_c| across 25-variant cohort: 0.18 → 0.07 (~60% reduction).
No regressions on the other 24 variants or any golden fixture —
gate keyed on Table 4a warm-air SAP code frozenset (only electric
2 in the corpus has a code in that set).
Tests: 905 pass (+1), 0 fail. Pyright net-zero (35 → 35).
Co-Authored-By: Claude Opus 4.7 <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 | ||
| 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