feat: add CAD calibration session configuration and manual check endpoint

tests/test_cad_calibration_engine.py

@@ -0,0 +1,76 @@
+import pytest
+
+from repeater.web.cad_calibration_engine import CADCalibrationEngine
+
+
+class _FakeRadio:
+    def __init__(self, responses):
+        self._responses = list(responses)
+        self.frequency = 868000000
+        self.spreading_factor = 8
+        self.bandwidth = 125000
+        self.coding_rate = 5
+
+    async def perform_cad(self, **kwargs):
+        if not self._responses:
+            return {"cad_done": True, "detected": False}
+        return self._responses.pop(0)
+
+
+@pytest.mark.asyncio
+async def test_test_cad_config_aggregates_detected_non_detected_timeout_error_counts():
+    engine = CADCalibrationEngine()
+    radio = _FakeRadio(
+        [
+            {"cad_done": True, "detected": True},
+            {"cad_done": True, "detected": False},
+            {"timeout": True, "detected": False},
+            {"error": "spi fault", "detected": False},
+            {"cad_done": True, "detected": True},
+        ]
+    )
+
+    result = await engine.test_cad_config(
+        radio, det_peak=22, det_min=10, samples=5, cad_symbol_num=2, cad_timeout_seconds=0.1
+    )
+
+    assert result["attempts"] == 5
+    assert result["detections"] == 2
+    assert result["non_detections"] == 1
+    assert result["timeouts"] == 1
+    assert result["errors"] == 1
+    assert result["cad_done_count"] == 3
+
+
+def test_get_test_ranges_is_small_and_centered():
+    engine = CADCalibrationEngine()
+    peaks, mins = engine.get_test_ranges(spreading_factor=8, base_peak=22, base_min=10)
+    assert peaks == [20, 21, 22, 23, 24]
+    assert mins == [9, 10, 11]
+
+
+def test_select_recommended_result_known_signal_prefers_higher_detection_rate():
+    engine = CADCalibrationEngine()
+    results = [
+        {"det_peak": 22, "det_min": 10, "detection_rate": 20.0, "timeouts": 0, "errors": 0},
+        {"det_peak": 23, "det_min": 10, "detection_rate": 60.0, "timeouts": 0, "errors": 0},
+    ]
+    recommended, reason = engine._select_recommended_result(
+        results, known_signal_present=True, sf=8
+    )
+    assert recommended["det_peak"] == 23
+    assert "known-signal" in reason
+
+
+def test_select_recommended_result_no_signal_prefers_low_false_detections_and_stability():
+    engine = CADCalibrationEngine()
+    results = [
+        {"det_peak": 22, "det_min": 10, "detection_rate": 0.0, "timeouts": 0, "errors": 0},
+        {"det_peak": 23, "det_min": 10, "detection_rate": 40.0, "timeouts": 0, "errors": 0},
+        {"det_peak": 24, "det_min": 10, "detection_rate": 0.0, "timeouts": 2, "errors": 0},
+    ]
+    recommended, reason = engine._select_recommended_result(
+        results, known_signal_present=False, sf=8
+    )
+    assert recommended["det_peak"] == 22
+    assert "Validation with a known compatible LoRa transmission is still required." in reason