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Contains projects associated to the development of modeling products
0728aa1039
SAP 10.2 Table 4f (PDF p.174) "Electricity for fans, pumps and other
auxiliary uses" — Heating system circulation pump rows:
Circulation pump, 2013 or later 41 kWh/yr
Circulation pump, 2012 or earlier 165 kWh/yr
Circulation pump, unknown date 115 kWh/yr
Pre-slice the cascade hardcoded `_PUMPS_FANS_KWH_BY_MAIN_CATEGORY[2]
= 160 kWh/yr` (115 Unknown CH + 45 gas flue fan) for category=2 gas
boilers and fell through to `_DEFAULT_PUMPS_FANS_KWH_PER_YR = 130`
for any other category. Both shortcuts ignored the per-cert
`central_heating_pump_age` lodging AND incorrectly applied
circulation pump electricity to dry electric storage / direct-acting
/ room heater systems (no primary water loop).
Implementation:
- Mapper: `_elmhurst_pump_age_int` now recognises both "Pre 2013"
and "2012 or earlier" string forms as the SAP10 enum 1 (Pre 2013).
Pre-slice "2012 or earlier" silently returned 2 (2013 or later)
on the entire oil corpus, mis-applying the 41 kWh post-2013
circulation pump to certs that lodge "2012 or earlier" via
Elmhurst Summary §14 "Heat pump age".
- New `_is_wet_boiler_main(main)` gate: identifies wet-boiler
systems by Table 4a/4b code range (101-141 gas/oil, 151-161
solid fuel, 191-196 electric boilers), PCDB Table 322 record,
or category ∈ {1, 2} fallback. Heat pumps (cat 4) return False
per Table 4f note "Not applicable for electric heat pumps from
database". Electric storage / direct / room heater codes
(401-499, 601-699) return False — they have no primary loop.
- New `_table_4f_circulation_pump_kwh(main)` dispatches on
`central_heating_pump_age`:
None / 0 → 115 kWh (Unknown date)
1 → 165 kWh (Pre 2013 / 2012 or earlier)
2 → 41 kWh (2013 or later)
- New `_table_4f_main_1_gas_boiler_flue_fan_kwh(main)` extracts
the gas-flue-fan 45 kWh logic from the old category dispatch.
Gated on `_is_wet_boiler_main` + gas fuel + fan_flue_present.
- Remove `_PUMPS_FANS_KWH_BY_MAIN_CATEGORY` and
`_DEFAULT_PUMPS_FANS_KWH_PER_YR` constants (the new helpers
replace both).
Worksheet evidence for the wet-boiler gate:
electric 1 (code 191 electric boiler): ws (230c) = 41 kWh ✓
electric 5 (code 402 electric storage): ws (231) = 0 kWh ✗
solid fuel 2 (code 158 anthracite): ws (230c) = 41 kWh ✓
solid fuel 9 (code 636 wood stove): ws (231) = 0 kWh ✗
oil 1 (code 127 condensing oil): ws (230c) = 165 kWh ✓
oil pcdb 3 (PCDB 18573): ws (230c) = 41 kWh ✓
Cascade impact across heating-systems corpus (vs S0380.148 state):
| Variant | SAP Δ | Cause |
|----------------|--------------|-------|
| oil 1 | +0.60→+0.40 | 165 + 100 = 265 ≡ worksheet exact |
| oil pcdb 1/2 | -0.15→+0.36 | 41 + 100 = 141 ≡ ws exact |
| oil pcdb 3 | +0.59→+0.39 | same |
| pcdb 1 | -0.03→+0.50 | 41 + 100 = 141 ≡ ws (was over) |
| electric 1 | -0.06→+0.45 | 41 (wet electric boiler) |
| electric 3-9 | -0.1..-1.4→ | 0 (dry storage/UFH) |
| | +0.5..+0.6 | was 130 default; now 0 |
| solid fuel 2-8 | various | 41 (boilers) — partial closures |
| solid fuel 9-11| -0.2→+0.5 | 0 (room heaters) — was 130 |
Re-pins reflect spec-correct application. Per
[[feedback-software-no-special-handling]]: pre-slice near-zero pins
were masking pre-existing offsetting cascade gaps; spec correctness
unmasks them.
Golden fixtures impact:
- cert 0240 (dual oil combi, pump_age=0 Unknown): PE +2.52→+2.18
- cert 0390 (Firebird PCDF oil, pump_age=0): PE -28.08→-28.27
- cert 6035 (gas combi, pump_age=2 post-2013): PE +47.29→+46.42
Cert 6035 closer to zero (post-2013 41 kWh < pre-slice 115 unknown).
Cert 0240/0390 small shifts from removing the gas-cat-2 hardcoded
160 path for oil mains.
Tests:
- test_sap_table_4f_circulation_pump_dispatches_per_central_heating_
pump_age — asserts oil 1 inputs.pumps_fans_kwh_per_yr == 265
(165 Pre 2013 + 100 liquid fuel) ± 1.0.
- test_sap_table_4f_liquid_fuel_boiler_flue_fan_and_fuel_pump_adds_
100_kwh (S0380.148) still passes.
Extended handover suite: 892 pass, 0 fail. Pyright net-improved
(removed unused `main_category` variable, file 33→32 errors).
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/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