Closes a systematic +0.02..+0.07 SAP over-prediction on every triple-
glazed cert in cohort 2 (13 of 38) and removes a silent-default
failure mode flagged via cert 3336-2825-9400-0512-8292 (+0.0674 Δ).
Root cause: `_map_elmhurst_window` (datatypes/epc/domain/mapper.py)
was passing the Elmhurst-lodged glazing-type string verbatim into
`SapWindow.glazing_type` (declared `Union[int, str]`). The §5 (66)..
(67) daylight-factor cascade at
`domain/sap10_calculator/worksheet/internal_gains.py:512` requires
`isinstance(w.glazing_type, int)` to look up Table 6b col light g_L —
string lodgings silently fell through to the `_G_LIGHT_DEFAULT = 0.80`
(double-glazed) branch. Cert 3336 (Triple glazed, worksheet "Window,
Triple glazed") got g_L = 0.80 instead of the correct 0.70, inflating
C_daylight from 1.072 to 1.041 → lighting kWh under-predicted by
−4.53 kWh/yr → total fuel cost under by −1.17 GBP → ECF Δ −0.0049 →
SAP continuous over by +0.0674.
Fix: `_ELMHURST_GLAZING_LABEL_TO_SAP10` dict + `_elmhurst_glazing_
type_code` helper translate the Elmhurst Summary §11 lodged strings
to the SAP 10.2 Table U2 integer codes the cascade keys on:
"Single" → 1
"Double pre 2002" → 2
"Double between 2002 and 2021" → 3
"Double with unknown install date" → 3
"Double with unknown 16 mm or install date more" → 3
"Double post or during 2022" → 5
"Triple post or during 2022" → 6
"Triple post or during" → 6 (year-trunc.)
"Secondary" → 7
Two regex passes strip the layout noise the extractor sometimes folds
into the glazing-type token: a `(?:Part )?value value Proofed Shutters`
prefix (from adjacent column headers) and a ` Summary Information` /
` Alternative wall…` suffix. Verified against the union of cohort-1
(7 certs) + cohort-2 (38 certs) + test-fixture (9 PDFs) glazing
labels: 18 distinct surface forms, all closed by the dict + noise
patterns; one window in cert 2636's Summary_000898.pdf lodged the
year-truncated "Triple post or during" — added as an alias for code 6
per worksheet "Triple glazed" lodging.
Strict-enum gate: `_elmhurst_glazing_type_code` raises
`UnmappedElmhurstLabel("glazing_type", label)` (Slice S0380.15
pattern, extended to the new helper) when the label is None or not
in the dict — surfaces mapper-coverage gaps at extraction time rather
than masking them as a SAP precision floor.
Cohort-2 Summary-path delta progression (38 certs):
bucket before slice 2 after slice 2
exact (<1e-4) 11 11
<0.005 0 5 ← 9421 +0.0012, 2536 +0.0016, 9370 +0.0017, 0100 +0.0028, 2800 +0.0044
0.005-0.07 15 10 ← all triple-glazed
0.07-0.5 5 5
0.5-1 4 4
1-5 1 1
5+ 2 2
RAISES 0 0
3336 (user's flag) closes from +0.0674 → +0.0400 — the residual is
the remaining systematic offset the next slice will investigate.
Tests added (3):
- `test_summary_3336_triple_glazed_windows_route_to_code_6` — pins
the mapper output for the user's flagged cert.
- `test_summary_000474_double_glazed_windows_route_to_code_3` —
exercises the DG branch + the year-unknown alias mapping.
- `test_summary_mapper_raises_on_unmapped_glazing_type_label` —
strict-enum coverage gate via mutated site notes.
Tests updated (1):
- `test_first_window_glazing_type` (test_elmhurst_end_to_end.py):
asserts int code 5 (DG low-E argon — "Double post or during 2022")
not the string verbatim. The string-passthrough behaviour was
always a latent bug; this test was the only direct pin on it.
Pyright net-zero per file:
- datatypes/epc/domain/mapper.py: 32 (baseline 32)
- backend/documents_parser/tests/test_summary_pdf_mapper_chain.py: 0
- backend/documents_parser/tests/test_elmhurst_end_to_end.py: 0
Regression baseline: 694 pass + 10 fail (= prior 691 + 10 + 3 new).
Triple-glazed original-cohort certs are now closer to worksheet too;
the ±0.07 chain tests on the original cohort still hold, and a future
slice tightens them once the next-largest residual is closed.
Spec refs:
- SAP 10.2 Table U2 — glazing-type integer enum.
- SAP 10.2 Table 6b col light — light-transmission g_L by glazing
type (triple 0.70, double-glazed variants 0.80, single 0.90).
- RdSAP 10 §11 Windows — Summary lodging of glazing type as a
type+install-date phrase.
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