Graham McIntire
e7a7ae073d
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.
80 lines
2.7 KiB
Elixir
80 lines
2.7 KiB
Elixir
defmodule Mix.Tasks.HrrrClimatology do
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@shortdoc "Build surface temperature climatology from hrrr_profiles"
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@moduledoc """
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Aggregates `hrrr_profiles.surface_temp_c` by (lat, lon, month, hour)
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into `hrrr_climatology` for use by the temperature-anomaly feature.
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Discovers which (month, hour) combos have data first, then processes
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only those batches. Idempotent via ON CONFLICT.
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mix hrrr_climatology # build from all grid-point profiles
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mix hrrr_climatology --min-samples 5 # require at least 5 observations per cell
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"""
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use Mix.Task
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alias Microwaveprop.Repo
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@impl Mix.Task
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def run(argv) do
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Mix.Task.run("app.start")
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Oban.pause_all_queues(Oban)
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{opts, _, _} = OptionParser.parse(argv, switches: [min_samples: :integer])
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min_samples = Keyword.get(opts, :min_samples, 3)
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# Discover which (month, hour) combos actually have data
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%{rows: combos} =
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Repo.query!(
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"""
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SELECT EXTRACT(MONTH FROM valid_time)::int AS month,
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EXTRACT(HOUR FROM valid_time)::int AS hour
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FROM hrrr_profiles
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WHERE surface_temp_c IS NOT NULL AND is_grid_point = true
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GROUP BY 1, 2
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ORDER BY 1, 2
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""",
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[],
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timeout: 120_000
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)
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Mix.shell().info("Building climatology (min_samples=#{min_samples}, #{length(combos)} batches)...")
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total =
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combos
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|> Enum.with_index(1)
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|> Enum.reduce(0, fn {[month, hour], idx}, acc ->
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%{num_rows: count} =
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Repo.query!(
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"""
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INSERT INTO hrrr_climatology (id, lat, lon, month, hour,
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mean_surface_temp_c, stddev_surface_temp_c, sample_count)
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SELECT gen_random_uuid(), lat, lon,
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$2 AS month,
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$3 AS hour,
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AVG(surface_temp_c),
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STDDEV_SAMP(surface_temp_c),
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COUNT(*)
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FROM hrrr_profiles
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WHERE surface_temp_c IS NOT NULL
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AND is_grid_point = true
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AND EXTRACT(MONTH FROM valid_time)::int = $2
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AND EXTRACT(HOUR FROM valid_time)::int = $3
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GROUP BY lat, lon
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HAVING COUNT(*) >= $1
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ON CONFLICT (lat, lon, month, hour)
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DO UPDATE SET
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mean_surface_temp_c = EXCLUDED.mean_surface_temp_c,
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stddev_surface_temp_c = EXCLUDED.stddev_surface_temp_c,
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sample_count = EXCLUDED.sample_count
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""",
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[min_samples, month, hour],
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timeout: 300_000
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)
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Mix.shell().info(" [#{idx}/#{length(combos)}] month=#{month} hour=#{hour}: #{count} rows")
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acc + count
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end)
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Mix.shell().info("Upserted #{total} climatology records total.")
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end
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end
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