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Contains projects associated to the development of modeling products
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SAP 10.2 §2 lines (17a)/(18) "Air permeability value, AP4 (m³/h/m²)" (PDF p.12-13): > "The air permeability at 4 Pa (AP4) measured with the low-pressure > pulse technique [...] is used in the following formula to estimate > of the air infiltration rate at typical pressure differences. > In this case (9) to (16) of the worksheet are not used." > > Air infiltration rate (ach) = 0.263 × AP4^0.924 > > If based on air permeability value at 4 Pa, > then (18) = [0.263 × (17a)^0.924] + (8) SAP 10.2 §2 lines (23a)/(24c)/(25) "MEV" + "Whole-house extract ventilation" (PDF p.13/133): > "The SAP calculation is based on a throughput of 0.5 air changes per > hour through the mechanical system." (23a) = 0.5 > > If whole house extract ventilation or positive input ventilation > from outside: > if (22b)m < 0.5 × (23b), then (24c) = (23b) > otherwise (24c) = (22b)m + 0.5 × (23b) Cert 000565 lodges: - Summary §12.1 "Mechanical Ventilation Type: Mechanical extract, decentralised (MEV dc)" (PCDF 500755) - Summary §12.2 "Test Method: Pulse" + "Pressure Test Result (AP4): 2.00" Pre-slice both lodgements were silently dropped by the Elmhurst extractor / mapper / `cert_to_inputs` cascade: - AP4 had no schema field on `VentilationAndCooling` or `SapVentilation` even though `ventilation.py:ventilation_from_inputs(air_permeability_ ap4=...)` already implemented the spec formula. - Mechanical Ventilation Type had no schema field; `cert_to_inputs. ventilation_from_cert` hardcoded `mv_kind=MechanicalVentilationKind. NATURAL` regardless of the lodgement, routing cert 000565 through the (24d) natural-vent formula instead of (24c). These bugs are coupled: AP4 alone would close (18) but the cascade's (25) NATURAL pass-through would then *under*-count the effective ach by 0.25 (the missing MEV contribution). MEV alone would over-count because the (18) over-count remains. Per [[feedback-bigger-slices- for-uniform-work]] + handover precedent on coupling-aware reverts, these land together. Slice span (5 layers): 1. **Schema** — `VentilationAndCooling.air_permeability_ap4_m3_h_m2` + `VentilationAndCooling.mechanical_ventilation_type` (site-notes); `SapVentilation.air_permeability_ap4_m3_h_m2` + `SapVentilation.mechanical_ventilation_kind` (domain). 2. **Extractor** — `_extract_ventilation` parses "Pressure Test Result (AP4)" scoped to §12.2 and "Mechanical Ventilation Type" scoped to §12.1. Both default to None when the cert lodges no MV / no Pulse test (cohort modal case). 3. **Mapper** — `_map_elmhurst_ventilation` plumbs AP4 through; new `_ELMHURST_MV_TYPE_TO_KIND` dispatch with strict-raise on unmapped labels (per [[reference-unmapped-elmhurst-label]] mirror pattern). 4. **cert_to_inputs** — `ventilation_from_cert` reads AP4 and resolves `mechanical_ventilation_kind` name → `MechanicalVentilationKind` enum. MEV/MV/MVHR kinds set `mv_system_ach=0.5` per spec (23a). 5. **Tests** — 4 in test_summary_pdf_mapper_chain.py (extractor + mapper for both AP4 and MEV kind), 2 in test_cert_to_inputs.py (cascade AP4 formula + MEV kind dispatch). All AAA-structured. Cert 000565 movement (HEAD `83218630` → this slice): - cascade (18) pressure_test_ach: 2.4037 → 2.0287 ✓ EXACT vs ws 2.0287 - cascade (21) shelter-adj: 2.0431 → 1.7244 ✓ EXACT vs ws 1.7244 - cascade mean (25)m: 2.2347 → 2.1360 vs ws 2.086 (+0.05) - **sap_score (integer): 28 → 29 ✓ EXACT vs ws 29** (Δ−1 → Δ 0) - sap_score_continuous: 27.99 → 28.77 (Δ−0.52 → +0.26) - ecf: 5.44 → 5.36 (Δ+0.05 → −0.03) - total_fuel_cost_gbp: 4726.75 → 4657.37 (Δ+46 → Δ−23) - co2_kg_per_yr: 6506.48 → 6415.56 (Δ+59 → Δ−32) - **space_heating_kwh: +631 → −367** (~75% closed) - main_heating_fuel: +371 → −216 (~58% closed) - hot_water_kwh: ✓ 0 EXACT unchanged - lighting / pumps_fans: sub-spec residuals unchanged The residual cascade-over-by-0.05 ach on (25)m is the cascade using the cert-agnostic Table U2 wind tuple instead of the cert's regional wind lookup; future ventilation_from_cert wires a `postcode_climate` arg through which `cert_to_demand_inputs` already does for the demand cascade, but the SAP-rating cascade keeps the Table U2 default. Cohort safety: - All 21 other Elmhurst cohort fixtures lodge `pressure_test_method= "Not available"` and `mechanical_ventilation=False` → both new fields default to None → cascade behaviour unchanged. - 9 golden + 38 cohort-2 API certs route through `_map_sap_ventilation` (the API mapper variant), which leaves both new SapVentilation fields at their None default → cascade behaviour unchanged. Test baseline: 582 pass + 8 expected `000565` fails (was 575 + 9; +6 new tests + sap_score reclassified from fail to pass). 1763 pass in broader sap10_ml + worksheet + epc.domain suites + 3 pre-existing fails unchanged. Pyright net-zero per touched file (1/0/0/32/34→32/13/ 11 → 1/0/0/32/32/13/11, cert_to_inputs.py improved −2). Per [[project-sap10_ml-deprecation]] the new fields live on the existing `SapVentilation` domain type; no new modules under sap10_ml. 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 | ||
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| sfr/principal_pitch | ||
| survey_report | ||
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| utils | ||
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| .dockerignore | ||
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| __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