161 lines
4.6 KiB
Python
161 lines
4.6 KiB
Python
from __future__ import annotations
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from datetime import datetime, timedelta, timezone
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import numpy as np
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import pandas as pd
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from app.services import burst_detection
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TARGET = datetime(2026, 6, 20, 5, 30, tzinfo=timezone.utc)
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def _complete_records(*, target: datetime, offset: float = 0.0) -> list[dict]:
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start = target - timedelta(days=15) + timedelta(minutes=15)
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return [
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{
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"time": (start + timedelta(minutes=15 * index)).isoformat(),
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"value": float(index % 96) + offset,
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}
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for index in range(15 * 96)
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]
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def test_build_target_pressure_aligns_timestamps_and_excludes_incomplete_sensor(
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monkeypatch,
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):
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nodes = [f"J{index}" for index in range(6)]
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mapping = {node: f"D{index}" for index, node in enumerate(nodes)}
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scada_data = {
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query_id: _complete_records(target=TARGET, offset=float(index))
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for index, query_id in enumerate(mapping.values())
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}
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scada_data["D5"] = scada_data["D5"][:-1]
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monkeypatch.setattr(
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burst_detection,
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"_get_pressure_sensor_mapping",
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lambda _network: mapping,
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)
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monkeypatch.setattr(
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burst_detection.InternalQueries,
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"query_latest_scada_time",
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lambda **_kwargs: TARGET,
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)
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monkeypatch.setattr(
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burst_detection.InternalQueries,
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"query_scada_by_ids_timerange",
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lambda **_kwargs: scada_data,
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)
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frame, resolved_target, excluded = (
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burst_detection._build_target_pressure_from_scada(
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network="test",
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sensor_nodes=nodes,
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requested_target_time=TARGET,
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sampling_interval_minutes=15,
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points_per_day=96,
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)
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)
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assert resolved_target == TARGET
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assert frame.shape == (1440, 5)
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assert frame.index[-1].to_pydatetime() == TARGET
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assert excluded == [
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{"sensor_node": "J5", "reason": "missing_or_invalid_samples"}
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]
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def test_target_mode_uses_fixed_parameters_and_only_classifies_target(monkeypatch):
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index = pd.date_range(
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start=TARGET - timedelta(days=15) + timedelta(minutes=15),
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end=TARGET,
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freq="15min",
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)
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values = np.tile(np.arange(96, dtype=float), 15)
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frame = pd.DataFrame(
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{f"J{sensor}": values + sensor for sensor in range(5)},
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index=index,
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)
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monkeypatch.setattr(
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burst_detection,
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"_get_pressure_sensor_nodes",
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lambda _network: list(frame.columns),
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)
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monkeypatch.setattr(
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burst_detection,
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"_build_target_pressure_from_scada",
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lambda **_kwargs: (frame, TARGET, []),
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)
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payload = burst_detection.run_burst_detection(
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network="test",
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username="tester",
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sampling_interval_minutes=15,
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)
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assert payload["target_time"] == TARGET.isoformat()
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assert payload["sample_count"] == 1440
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assert payload["points_per_day"] == 96
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assert payload["algorithm_params"]["mu"] == 1
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assert payload["summary"]["score_threshold"] == -0.04
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assert [row["Role"] for row in payload["rows"]].count("target") == 1
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assert all(not row["IsBurst"] for row in payload["rows"][:-1])
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assert payload["reference_window"] == {
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"start": (TARGET - timedelta(days=14)).isoformat(),
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"end": (TARGET - timedelta(days=1)).isoformat(),
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"day_count": 14,
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}
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def test_sampling_interval_uses_scada_frequency_and_can_be_overridden(monkeypatch):
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monkeypatch.setattr(
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burst_detection,
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"get_all_scada_info",
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lambda _network: [
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{
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"type": "pressure",
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"associated_element_id": "J1",
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"transmission_frequency": "0:15:00",
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},
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{
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"type": "pressure",
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"associated_element_id": "J2",
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"transmission_frequency": "0:15:00",
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},
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],
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)
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assert (
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burst_detection._resolve_sampling_interval_minutes(
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network="test",
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sensor_nodes=["J1", "J2"],
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requested_interval=None,
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)
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== 15
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)
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assert (
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burst_detection._resolve_sampling_interval_minutes(
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network="test",
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sensor_nodes=["J1", "J2"],
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requested_interval=30,
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)
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== 30
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)
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def test_target_threshold_is_applied_only_to_latest_row():
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result = pd.DataFrame(
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{
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"Day": [1, 2, 3],
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"Score": [-0.3, -0.2, -0.04],
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"Prediction": [-1, -1, 1],
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"IsBurst": [True, True, False],
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}
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)
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rows = burst_detection._serialize_result_rows(result, target_only=True)
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assert [row["IsBurst"] for row in rows] == [False, False, True]
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