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Author	SHA1	Message	Date
Graham McIntire	e7a7ae073d	Phase 9.3, 9.4, and Phase 3 NEXRAD pipeline Task 9.3 - Weight recalibration via gradient descent: - Recalibrator module fits logistic regression weights using Nx - Trains on QSO positives vs random baseline negatives - Cross-validates by month, normalizes weights to sum to 1.0 - Mix task: mix recalibrate_scorer --sample 5000 --epochs 2000 Task 9.4 - Side-by-side scorer comparison: - ScorerDiff.compare/3 re-scores grid with old vs new weights - Reports mean diff, regressions, improvements, per-band breakdown - Mix task: mix scorer_diff --new-weights '{...}' Phase 3 - NEXRAD ingestion pipeline: - NexradClient fetches IEM n0q composite PNGs, extracts per-point box statistics (mean/max dBZ, texture variance) - NexradObservation schema with unique (lat, lon, observed_at) - NexradWorker on :nexrad queue for background processing - nexrad_texture backtest feature in Features module - mix nexrad_backfill --limit 200 All tasks added to AdminTaskWorker and Release for production use. 1116 tests, 0 failures.	2026-04-10 12:48:36 -05:00
Graham McIntire	6d92973853	Phase 9.1: Consolidated backtest report and contest log import - Add `mix backtest --all` for consolidated pass/fail table across all features - Add Backtest.consolidated_report/2 and to_consolidated_markdown/1 - Add Features.all_features/0 to auto-discover backtestable features - Add `mix import_contest_logs` for bulk ARRL contest CSV import with dedup - Fix hrrr_climatology to batch by (month, hour) to avoid query timeout - Fix Repo.query! result pattern (Postgrex.Result, not tuple) - Backtest reports for all Phase 1-6 features	2026-04-10 11:57:15 -05:00
Graham McIntire	ab04cb9168	Phase 0: backtest harness Add Microwaveprop.Backtest: a feature-evaluation framework that runs a (lat, lon, valid_time) -> float function over the historical QSO corpus and a matched random-time baseline, reporting distribution statistics, distance-binned lift, and band-stratified lift. Adds four baseline feature wrappers around the current scorer inputs (naive_gradient, td_depression, time_of_day, pressure), a mix backtest CLI, and the first set of baseline reports under priv/backtest_reports so downstream phases have a frozen reference point to compare against.	2026-04-09 16:10:54 -05:00

Author

SHA1

Message

Date

Graham McIntire

e7a7ae073d

Phase 9.3, 9.4, and Phase 3 NEXRAD pipeline

Task 9.3 - Weight recalibration via gradient descent:
- Recalibrator module fits logistic regression weights using Nx
- Trains on QSO positives vs random baseline negatives
- Cross-validates by month, normalizes weights to sum to 1.0
- Mix task: mix recalibrate_scorer --sample 5000 --epochs 2000

Task 9.4 - Side-by-side scorer comparison:
- ScorerDiff.compare/3 re-scores grid with old vs new weights
- Reports mean diff, regressions, improvements, per-band breakdown
- Mix task: mix scorer_diff --new-weights '{...}'

Phase 3 - NEXRAD ingestion pipeline:
- NexradClient fetches IEM n0q composite PNGs, extracts per-point
  box statistics (mean/max dBZ, texture variance)
- NexradObservation schema with unique (lat, lon, observed_at)
- NexradWorker on :nexrad queue for background processing
- nexrad_texture backtest feature in Features module
- mix nexrad_backfill --limit 200

All tasks added to AdminTaskWorker and Release for production use.
1116 tests, 0 failures.

2026-04-10 12:48:36 -05:00

Graham McIntire

6d92973853

Phase 9.1: Consolidated backtest report and contest log import

- Add `mix backtest --all` for consolidated pass/fail table across all features
- Add Backtest.consolidated_report/2 and to_consolidated_markdown/1
- Add Features.all_features/0 to auto-discover backtestable features
- Add `mix import_contest_logs` for bulk ARRL contest CSV import with dedup
- Fix hrrr_climatology to batch by (month, hour) to avoid query timeout
- Fix Repo.query! result pattern (Postgrex.Result, not tuple)
- Backtest reports for all Phase 1-6 features

2026-04-10 11:57:15 -05:00

Graham McIntire

ab04cb9168

Phase 0: backtest harness

Add Microwaveprop.Backtest: a feature-evaluation framework that runs
a (lat, lon, valid_time) -> float function over the historical QSO
corpus and a matched random-time baseline, reporting distribution
statistics, distance-binned lift, and band-stratified lift.

Adds four baseline feature wrappers around the current scorer inputs
(naive_gradient, td_depression, time_of_day, pressure), a mix backtest
CLI, and the first set of baseline reports under priv/backtest_reports
so downstream phases have a frozen reference point to compare against.

2026-04-09 16:10:54 -05:00

3 commits