from __future__ import annotations
import numpy as np, h5py

from sfm.database import SeismoDb
from sfm.waveform_store import WaveformStore
from scripts.backfill_event_shape import backfill_shape
from minimateplus.models import Event


def _h5(path, long):
    with h5py.File(path, "w") as f:
        g = f.create_group("samples")
        for k in ("Tran", "Vert"):
            g.create_dataset(k, data=np.zeros(1024, "float32"))
        g.create_dataset("Long", data=np.asarray(long, "float32"))


def test_backfill_updates_shape_and_is_idempotent(tmp_path):
    db = SeismoDb(tmp_path / "s.db")
    store = WaveformStore(tmp_path / "waveforms")
    ev = Event(index=0)
    ev._waveform_key = bytes.fromhex("0111abcd")
    db.insert_events([ev], serial="BE1",
                     waveform_records={ev._waveform_key.hex():
                                       {"filename": "F.CE0W", "filesize": 10}})
    # place the .h5 where store.paths_for expects it
    long = np.zeros(1024); long[100] = 0.48
    _h5(store.hdf5_path_for("BE1", "F.CE0W"), long)

    c1 = backfill_shape(db, store)
    assert c1["updated"] == 1
    row = db.query_events(serial="BE1")[0]
    assert row["shape_axis"] == "Long" and row["shape_near_peak_count"] <= 3
    c2 = backfill_shape(db, store)                  # idempotent: re-run overwrites same values
    assert db.query_events(serial="BE1")[0]["shape_crest_factor"] == row["shape_crest_factor"]