f546bd5ddc
Adds two Layer-4 chain tests for the ASHP cohort, both pinning at the
±0.07 spec-floor tolerance with **zero new mapper slices required**.
The structural debt paid down in S0380.2..S0380.9 (HP routing,
cylinder block, composite walls, multi-array PV, multi-bp extension
wall_insulation_thickness inheritance) was already sufficient for
these two certs — they close first-try.
First-attempt probe results across the 5 remaining ASHP cohort certs:
cert Worksheet Summary-cascade Δ in floor?
2225 88.7921 88.4842 -0.3079 no
2636 86.2641 86.7514 +0.4873 no
3800 86.1458 86.1900 +0.0442 **YES** ← this slice
9285 84.1369 84.1871 +0.0502 **YES** ← this slice
9418 84.6305 87.2278 +2.5973 no (Daikin)
This is the strongest evidence yet that the Summary mapper has
amortized its variant-debt for standard single-bp / single-array
Mitsubishi-cohort ASHPs. Per the [[project-summary-path-cohort-
closure]] memory: 0380 needed 6 slices; 0350 needed 2; 3800 and 9285
need ZERO; 2225 / 2636 / 9418 each need ≤2-3 small slices to close.
Also adds the 5 remaining ASHP cohort Summary PDFs as fixtures
(Summary_000898, 000900, 000901, 000902, 000904) — copied from
`sap worksheets/Additional data with api/<cert>/`. The 3 not-yet-
closed certs (2225, 2636, 9418) will pick up chain tests in
subsequent slices once their per-cert gaps are paid down.
Pyright: 0 errors on the test file (no other code touched).
Regression suite: 679 pass + 10 fail (= handover baseline 669 + 10
+ 10 new GREEN tests across Slices S0380.2..S0380.10). Of the 10
new tests, 7 are unit-level mapper-boundary pins and 4 are chain
tests at ±0.07 (certs 0380, 0350, 3800, 9285).
Spec / precedent refs:
- Slice 102f (commit
|
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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