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https://github.com/pyMC-dev/pyMC_Repeater.git
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77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
import pytest
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from repeater.web.cad_calibration_engine import CADCalibrationEngine
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class _FakeRadio:
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def __init__(self, responses):
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self._responses = list(responses)
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self.frequency = 868000000
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self.spreading_factor = 8
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self.bandwidth = 125000
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self.coding_rate = 5
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async def perform_cad(self, **kwargs):
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if not self._responses:
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return {"cad_done": True, "detected": False}
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return self._responses.pop(0)
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@pytest.mark.asyncio
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async def test_test_cad_config_aggregates_detected_non_detected_timeout_error_counts():
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engine = CADCalibrationEngine()
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radio = _FakeRadio(
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[
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{"cad_done": True, "detected": True},
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{"cad_done": True, "detected": False},
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{"timeout": True, "detected": False},
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{"error": "spi fault", "detected": False},
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{"cad_done": True, "detected": True},
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]
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)
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result = await engine.test_cad_config(
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radio, det_peak=22, det_min=10, samples=5, cad_symbol_num=2, cad_timeout_seconds=0.1
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)
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assert result["attempts"] == 5
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assert result["detections"] == 2
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assert result["non_detections"] == 1
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assert result["timeouts"] == 1
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assert result["errors"] == 1
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assert result["cad_done_count"] == 3
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def test_get_test_ranges_is_small_and_centered():
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engine = CADCalibrationEngine()
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peaks, mins = engine.get_test_ranges(spreading_factor=8, base_peak=22, base_min=10)
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assert peaks == [20, 21, 22, 23, 24]
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assert mins == [9, 10, 11]
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def test_select_recommended_result_known_signal_prefers_higher_detection_rate():
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engine = CADCalibrationEngine()
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results = [
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{"det_peak": 22, "det_min": 10, "detection_rate": 20.0, "timeouts": 0, "errors": 0},
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{"det_peak": 23, "det_min": 10, "detection_rate": 60.0, "timeouts": 0, "errors": 0},
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]
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recommended, reason = engine._select_recommended_result(
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results, known_signal_present=True, sf=8
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)
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assert recommended["det_peak"] == 23
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assert "known-signal" in reason
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def test_select_recommended_result_no_signal_prefers_low_false_detections_and_stability():
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engine = CADCalibrationEngine()
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results = [
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{"det_peak": 22, "det_min": 10, "detection_rate": 0.0, "timeouts": 0, "errors": 0},
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{"det_peak": 23, "det_min": 10, "detection_rate": 40.0, "timeouts": 0, "errors": 0},
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{"det_peak": 24, "det_min": 10, "detection_rate": 0.0, "timeouts": 2, "errors": 0},
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]
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recommended, reason = engine._select_recommended_result(
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results, known_signal_present=False, sf=8
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)
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assert recommended["det_peak"] == 22
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assert "Validation with a known compatible LoRa transmission is still required." in reason
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