64 lines
2 KiB
Python
64 lines
2 KiB
Python
"""Whittaker S2 GCC (λ=400 d²) as a spatial constant vs withheld S2 GCC; crossover vs fusion nse_s2."""
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from __future__ import annotations
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from pathlib import Path
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from metrics_stats import (
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WHITTAKER_LAMBDA_DAYS_SQ,
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_norm_date_key,
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_s2_gcc_series_from_preselection,
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_whittaker_smooth_dict,
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)
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def whittaker_gcc_on_gap_masked_series(
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base: Path,
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strategy: str,
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prediction_iso: str,
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withheld_iso: str,
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lam: float = WHITTAKER_LAMBDA_DAYS_SQ,
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) -> float | None:
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"""Whittaker smooth on cloud-screened S2 GCC **excluding** the withheld acquisition day.
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Comparator aligned with ``baseline.s2_whittaker_lambda400`` in ``metrics_stats`` (same λ,
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same preselection GCC), but the withheld date is removed so the smoother does not see
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the target acquisition. Value at ``prediction_iso`` (YYYY-MM-DD) is returned.
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"""
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pred_k = _norm_date_key(prediction_iso)
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wh_k = _norm_date_key(withheld_iso)
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if not pred_k or not wh_k:
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return None
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all_gcc, flags = _s2_gcc_series_from_preselection(base)
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if not all_gcc:
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return None
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idx = 0 if strategy == "aggressive" else 1
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kept = sorted(
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(d, g)
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for d, g in all_gcc.items()
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if d in flags and not flags[d][idx] and _norm_date_key(d) != wh_k
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)
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if len(kept) < 2:
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return None
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obs_d, obs_v = zip(*kept)
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smooth = _whittaker_smooth_dict(obs_d, obs_v, lam)
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return smooth.get(pred_k)
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def first_gap_where_fusion_below_whittaker(
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rows: list[dict],
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*,
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fusion_key: str = "nse_s2",
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whittaker_key: str = "nse_s2",
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) -> int | None:
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"""Smallest ``gap_days`` where fusion[metric] < whittaker[metric] (strict)."""
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eligible = [
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r
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for r in rows
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if r.get(fusion_key) is not None and r.get(whittaker_key) is not None
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]
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eligible.sort(key=lambda r: r["gap_days"])
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for r in eligible:
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if r[fusion_key] < r[whittaker_key]:
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return int(r["gap_days"])
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return None
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