a05ecacd67
Mapper-drop audit across the 9-fixture cohort: `percent_draughtproofed`
is lodged on 9/9 certs (raw values 85-100) but the schema-21.0.1
mapper never set it on EpcPropertyData. The site-notes mappers always
have (line 312 of mapper.py); only the API path was missing.
cert_to_inputs reads `epc.percent_draughtproofed` for the §2
ventilation cascade (window draught loss); with None → 0 default, the
calc was treating every API-routed cert as fully draughty —
over-counting draught infiltration on every fixture in the cohort.
Fix: `percent_draughtproofed=schema.percent_draughtproofed` in
`from_rdsap_schema_21_0_1`.
Cohort SAP / PE / CO2 shifts (all 9 fixtures move; many shift one
SAP point because the continuous SAP was near a rounding boundary):
cert old SAP new SAP PE shift CO2 shift
0240-0200-5706-2365-8010 -12 -10 -7.63 -0.39
0300-2747-7640-2526-2135 -9 -7 -6.36 -0.55
0390-2254-6420-2126-5561 (LN12) 0 +1 -9.10 -0.13
0390-2954-3640-2196-4175 -7 -4 -4.87 -0.44
2130-1033-4050-5007-8395 (DE22) +8 +9 -3.67 -0.04
6035-7729-2309-0879-2296 -6 -5 -8.90 -0.21
7536-3827-0600-0600-0276 +3 +4 -9.19 -0.24
8135-1728-8500-0511-3296 +1 +1 (cont -7.48 -0.14
72.7→73.5)
9390-2722-3520-2105-8715 +2 +3 -7.32 -0.01
LN12 lost its exact-SAP-match (0 → +1, continuous 65.47 → 66.28); the
other fixtures' rounded SAP residuals tightened or worsened by 1
depending on which side of the rounding boundary they sit. This is
spec-correctness over residual-tightness: the lodged value is correct,
our calc now reads it.
930/930 Elmhurst cascade green. 78/78 mapper tests + 14/14 golden
cohort + PCDB chain green. Pyright net-zero.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| docs | ||
| epr_data_exports | ||
| etl | ||
| infrastructure/terraform | ||
| model_data/requirements | ||
| packages | ||
| recommendations | ||
| scripts | ||
| services | ||
| sfr/principal_pitch | ||
| survey_report | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| AGENTS.md | ||
| 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_backlog.sh | ||
| 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