2569718930@qq.com
46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
from scripts.fit_probability_calibration import _extract_samples
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def test_extract_samples_prefers_snapshot_rows_for_same_city_day():
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history = {
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"ankara": {
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"2026-03-19": {
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"actual_high": 11.0,
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"mu": 10.8,
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"deb_prediction": 10.9,
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"forecasts": {"ECMWF": 10.5, "GFS": 11.2},
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"probability_features": {
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"ens_median": 10.7,
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"ensemble_spread": 0.8,
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"peak_status": "before",
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},
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}
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}
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}
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snapshot_rows = [
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{
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"city": "ankara",
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"date": "2026-03-19",
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"timestamp": "2026-03-19T12:00:00+03:00",
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"raw_mu": 11.2,
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"raw_sigma": 1.1,
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"deb_prediction": 11.0,
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"ensemble": {"p10": 10.0, "median": 11.1, "p90": 12.2},
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"multi_model": {"ECMWF": 10.5, "GFS": 11.2},
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"max_so_far": 10.9,
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"peak_status": "in_window",
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}
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]
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samples, filled = _extract_samples(
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history,
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settlement_history={},
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snapshot_rows=snapshot_rows,
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)
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assert filled == 0
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assert len(samples) == 1
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assert samples[0]["sample_source"] == "snapshot"
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assert samples[0]["raw_mu"] == 11.2
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assert samples[0]["peak_flag"] == 0.5
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