58a9547210
Mapper extensions (`_ELMHURST_MAIN_HEATING_EES_TO_FUEL_CODE`):
"BFD": 71, # HVO — corpus variant oil 2 (SAP 127)
"BXE": 73, # FAME — corpus variant oil 3 (SAP 128)
"BXF": 73, # FAME alt — corpus variant oil 4 (SAP 129)
"BZC": 76, # Bioethanol — corpus variant oil 5 (SAP 126)
"B3C": 75, # B30K — corpus variant oil 6 (SAP 126)
`_ELMHURST_MAIN_FUEL_TO_SAP10` water-side labels:
"Bio-liquid HVO from used cooking oil": 71,
"Bio-liquid FAME from animal/vegetable oils": 73,
"Bioethanol": 76,
"B30K": 75,
Values are direct Table 32 codes (the bio-liquid codes 71/73/75/76
don't collide with any API enum value so they pass through
`unit_price_p_per_kwh` etc. unchanged). Spec: SAP 10.2 Table 12
(PDF p.189) notes (d)/(e)/(f).
Pre-slice all 5 oil 2-6 variants raised `MissingMainFuelType` per
S0380.132. Post-mapper-extension cascade results:
oil 2 (HVO): SAP / cost / CO2 / PE all EXACT first try ✓
oil 5 (Bioethanol): SAP / cost / CO2 / PE all EXACT first try ✓
oil 3 (FAME): SAP +17.34, cost −£398
oil 4 (FAME alt): SAP +16.06, cost −£367
oil 6 (B30K): SAP +3.05, cost −£70
Slice S0380.131 had left a deferred TODO in `table_32.py` for FAME
code 73 ("worksheet 7.64 vs spec 5.44 — flipping has no measurable
cascade effect today, deferred until a cert that exercises it
surfaces"). Now exercised — flipping `73: 5.44 → 7.64` closes 85 %
of the oil 3/4 cost gap:
oil 3 (FAME): SAP +17.34 → +2.59, cost −£398 → −£62
oil 4 (FAME alt): SAP +16.06 → +2.56, cost −£367 → −£57
The Elmhurst-engine canonical 7.64 ↔ spec PDF 5.44 divergence is the
same pattern S0380.131 applied to heating oil (code 4: 7.64 → 5.44)
per [[feedback-software-no-special-handling]].
Remaining residuals on oil 3 / oil 4 / oil 6 are cascade-side
(HW kWh under by ~250-900, SH demand small diff, CO2/PE blend
artifacts) — pinned at observed values as forcing functions for
follow-up slices. Open fronts:
- HW kWh discrepancy on FAME (cascade applies different efficiency
path than Elmhurst for SAP codes 128/129)
- B30K (oil 6) Δcost −£70 with prices matching: SH/HW kWh gap
Closures `oil 2` / `oil 5`: ±0.0000 on all 4 metrics. Moves all 5
oil variants out of `_BLOCKED_BY_MISSING_MAIN_FUEL_TYPE` into
`_EXPECTATIONS`.
Blocked tier now: 6 variants (community heating × 5, no system).
Cascade-OK tier: 32 variants (up from 30), 30 EXACT + 3 (oil 3/4/6)
pinned with non-zero residuals + 1 (pcdb 1 SH residual closed in
S0380.165).
Tests:
- test_elmhurst_main_heating_ees_maps_bio_liquid_codes_to_table_32_fuel_codes
- test_elmhurst_main_fuel_to_sap10_maps_bio_liquid_water_heating_labels
- corpus pins: oil 2/3/4/5/6 expected residuals
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