prop/lib/microwaveprop/workers/admin_task_worker.ex

defmodule Microwaveprop.Workers.AdminTaskWorker do
  @moduledoc """
  Oban worker for long-running admin tasks (backtests, climatology, etc).

  Enqueued via `Microwaveprop.Release` so that `eval` returns immediately
  and the work runs in the normal Oban pipeline without blocking.

  Each task type is dispatched by the `"task"` arg:

      Microwaveprop.Workers.AdminTaskWorker.new(%{task: "backtest_all"})
      Microwaveprop.Workers.AdminTaskWorker.new(%{task: "backtest", feature: "naive_gradient"})
      Microwaveprop.Workers.AdminTaskWorker.new(%{task: "climatology", min_samples: 3})
      Microwaveprop.Workers.AdminTaskWorker.new(%{task: "native_derive", limit: 10000})
  """
  use Oban.Worker, queue: :admin, max_attempts: 1, unique: [period: 60]

  import Ecto.Query

  alias Microwaveprop.Backtest
  alias Microwaveprop.Backtest.Features
  alias Microwaveprop.Propagation.Duct
  alias Microwaveprop.Propagation.Inversion
  alias Microwaveprop.Propagation.Recalibrator
  alias Microwaveprop.Repo
  alias Microwaveprop.Weather.HrrrNativeProfile
  alias Microwaveprop.Weather.ThetaE

  require Logger

  @impl Oban.Worker
  def perform(%Oban.Job{args: %{"task" => "backtest_all"} = args}) do
    sample_size = Map.get(args, "sample_size", 5000)
    features = Features.all_features()

    Logger.info("AdminTask: running consolidated backtest for #{map_size(features)} features")

    results = Backtest.consolidated_report(features, sample_size: sample_size)
    markdown = Backtest.to_consolidated_markdown(results)

    path = "priv/backtest_reports/consolidated.md"
    File.mkdir_p!(Path.dirname(path))
    File.write!(path, markdown)

    Logger.info("AdminTask: consolidated backtest complete, wrote #{path}")
    :ok
  end

  def perform(%Oban.Job{args: %{"task" => "backtest", "feature" => feature_name} = args}) do
    sample_size = Map.get(args, "sample_size", 5000)

    # `function_exported?/3` returns false for any module that hasn't
    # been loaded yet in the BEAM — force-load `Features` first so valid
    # feature names aren't rejected on a cold VM. Using
    # `String.to_existing_atom/1` inside a rescue guards against
    # unbounded atom creation (the admin UI is the only dispatcher, but
    # cheap insurance).
    with true <- Code.ensure_loaded?(Features),
         {:ok, fun_atom} <- safe_to_existing_atom(feature_name),
         true <- function_exported?(Features, fun_atom, 3) do
      run_backtest(feature_name, fun_atom, sample_size)
    else
      _ ->
        Logger.error("AdminTask: unknown feature #{feature_name}")
        {:error, "unknown feature: #{feature_name}"}
    end
  end

  def perform(%Oban.Job{args: %{"task" => "climatology"} = args}) do
    min_samples = Map.get(args, "min_samples", 3)

    %{rows: combos} =
      Repo.query!(
        """
        SELECT EXTRACT(MONTH FROM valid_time)::int AS month,
               EXTRACT(HOUR FROM valid_time)::int AS hour
        FROM hrrr_profiles
        WHERE surface_temp_c IS NOT NULL AND is_grid_point = true
        GROUP BY 1, 2
        ORDER BY 1, 2
        """,
        [],
        timeout: 120_000
      )

    Logger.info("AdminTask: building climatology (min_samples=#{min_samples}, #{length(combos)} batches)")

    total =
      combos
      |> Enum.with_index(1)
      |> Enum.reduce(0, fn {[month, hour], idx}, acc ->
        %{num_rows: count} =
          Repo.query!(
            """
            INSERT INTO hrrr_climatology (id, lat, lon, month, hour,
                                          mean_surface_temp_c, stddev_surface_temp_c, sample_count)
            SELECT gen_random_uuid(), lat, lon,
                   $2 AS month,
                   $3 AS hour,
                   AVG(surface_temp_c),
                   STDDEV_SAMP(surface_temp_c),
                   COUNT(*)
            FROM hrrr_profiles
            WHERE surface_temp_c IS NOT NULL
              AND is_grid_point = true
              AND EXTRACT(MONTH FROM valid_time)::int = $2
              AND EXTRACT(HOUR FROM valid_time)::int = $3
            GROUP BY lat, lon
            HAVING COUNT(*) >= $1
            ON CONFLICT (lat, lon, month, hour)
            DO UPDATE SET
              mean_surface_temp_c = EXCLUDED.mean_surface_temp_c,
              stddev_surface_temp_c = EXCLUDED.stddev_surface_temp_c,
              sample_count = EXCLUDED.sample_count
            """,
            [min_samples, month, hour],
            timeout: 300_000
          )

        if rem(idx, 10) == 0, do: Logger.info("AdminTask: climatology [#{idx}/#{length(combos)}]")
        acc + count
      end)

    Logger.info("AdminTask: climatology complete, upserted #{total} records")
    :ok
  end

  def perform(%Oban.Job{args: %{"task" => "native_derive"} = args}) do
    limit = Map.get(args, "limit", 10_000)

    profiles =
      HrrrNativeProfile
      |> where([p], is_nil(p.bulk_richardson) and p.level_count > 2)
      |> limit(^limit)
      |> Repo.all()

    Logger.info("AdminTask: deriving fields for #{length(profiles)} native profiles")

    count =
      Enum.count(profiles, fn profile ->
        p = %{
          heights_m: profile.heights_m,
          temp_k: profile.temp_k,
          spfh: profile.spfh,
          pressure_pa: profile.pressure_pa,
          u_wind_ms: profile.u_wind_ms,
          v_wind_ms: profile.v_wind_ms,
          tke_m2s2: profile.tke_m2s2,
          level_count: profile.level_count
        }

        inversion_fields =
          case Inversion.find_inversion_top(p) do
            {:ok, %{height_m: top_h, level_idx: top_idx, base_idx: base_idx}} ->
              [
                inversion_top_m: top_h,
                bulk_richardson: Inversion.bulk_richardson(p, base_idx, top_idx),
                shear_at_top_ms: Inversion.shear_magnitude(p, base_idx, top_idx),
                theta_e_jump_k: ThetaE.theta_e_jump(p, base_idx, top_idx)
              ]

            :none ->
              [inversion_top_m: nil, bulk_richardson: nil, shear_at_top_ms: nil, theta_e_jump_k: nil]
          end

        duct_result = Duct.analyze(p)
        fields = inversion_fields ++ [ducts: duct_result.ducts, best_duct_band_ghz: duct_result.best_duct_band_ghz]

        {1, _} =
          HrrrNativeProfile
          |> where([pr], pr.id == ^profile.id)
          |> Repo.update_all(set: fields)

        true
      end)

    Logger.info("AdminTask: derived fields for #{count} profiles")
    :ok
  end

  def perform(%Oban.Job{args: %{"task" => "recalibrate"} = args}) do
    sample_size = Map.get(args, "sample_size", 5000)
    epochs = Map.get(args, "epochs", 2000)
    learning_rate = Map.get(args, "learning_rate", 0.01)

    Logger.info("AdminTask: running weight recalibration (sample=#{sample_size}, epochs=#{epochs}, lr=#{learning_rate})")

    result =
      Recalibrator.fit(
        sample_size: sample_size,
        epochs: epochs,
        learning_rate: learning_rate
      )

    Logger.info("AdminTask: recalibration complete")

    Logger.info("  train_loss=#{result.train_loss}, val_loss=#{result.val_loss}, initial_loss=#{result.initial_loss}")

    for {factor, weight} <- Enum.sort(result.weights) do
      Logger.info("  #{factor}: #{weight}")
    end

    :ok
  end

  def perform(%Oban.Job{args: %{"task" => "scorer_diff"}}) do
    # scorer_diff was a calibration tool that read the per-cell
    # factors JSONB from the propagation_scores table. That table is
    # gone — factors are no longer persisted across the CONUS grid —
    # so the diff has nothing to compute against. Left as a no-op so
    # any in-flight Oban rows from the pre-cutover era drain cleanly.
    Logger.warning("AdminTask: scorer_diff is disabled — propagation_scores table + factors storage have been dropped")

    :ok
  end

  def perform(%Oban.Job{args: %{"task" => task}}) do
    Logger.error("AdminTask: unknown task #{task}")
    {:error, "unknown task: #{task}"}
  end

  defp safe_to_existing_atom(name) do
    {:ok, String.to_existing_atom(name)}
  rescue
    ArgumentError -> :error
  end

  defp run_backtest(feature_name, fun_atom, sample_size) do
    feature_fun = &apply(Features, fun_atom, [&1, &2, &3])
    name = "Microwaveprop.Backtest.Features.#{feature_name}"

    Logger.info("AdminTask: running backtest for #{feature_name}")

    report = Backtest.evaluate(feature_fun, sample_size: sample_size, feature_name: name)
    distance_bins = Backtest.lift_by_distance(feature_fun, sample_size: sample_size)
    band_stats = Backtest.lift_by_band(feature_fun, sample_size: sample_size)
    markdown = Backtest.to_markdown(report, distance_bins: distance_bins, band_stats: band_stats)

    path = "priv/backtest_reports/#{feature_name}.md"
    File.mkdir_p!(Path.dirname(path))
    File.write!(path, markdown)

    Logger.info("AdminTask: backtest for #{feature_name} complete, wrote #{path}")
    :ok
  end
end