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Adds coordinates: Optional[Coordinates] to Comparable and PredictionTarget
(data carriers — the pure predictor stays IO-free), and wires load_corpus to
read an optional _coordinates.json sidecar ({uprn: [lon, lat]}) and populate
each Comparable from its cert's uprn; iter_predictions threads the held-out
target's coordinates through. Absent sidecar -> geo-weighting stays off (no
behaviour change yet — weighting lands next slice). fetch_corpus_coordinates
now writes the sidecar into the corpus dir. load_corpus populates 99% of
corpus comparables.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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|---|---|---|
| .. | ||
| eon | ||
| analyse_api_sap_clusters.py | ||
| build_epc_prediction_fixture.py | ||
| decompose_api_cost_error.py | ||
| download_cotality_evidence.py | ||
| elmhurst_input_sheet.py | ||
| eval_api_sap_accuracy.py | ||
| fetch_2026_epc_sample.py | ||
| fetch_cohort2_api_jsons.py | ||
| fetch_corpus_coordinates.py | ||
| fetch_epc_bulk_sample.py | ||
| fetch_epc_dump.py | ||
| fetch_epc_prediction_corpus.py | ||
| historic_epc_demo.py | ||
| init_db.py | ||
| profile_api_error.py | ||
| rename_sharepoint_files.py | ||
| run_audit_generator_local.py | ||
| run_modelling_cohort.py | ||
| run_modelling_e2e.py | ||
| run_property_report.py | ||
| sero_address_list.csv | ||
| validate_epc_prediction.py | ||