meshcore-open/test/services/timeout_prediction_service_test.dart
zjs81 b336aedbc5 fix: address PR #296 code review feedback
- Clamp ML predictions between physics floor (raw airtime) and ceiling
  (worst-case formula) so model can never produce unsafe timeouts
- Replace hourOfDay feature with secondsSinceLastRx for network activity
- Remove unused _ContactStats.stdDev and dead model persistence code
- Debounce observation writes (2s) instead of writing on every delivery
- Skip recording observations when pathLength is null to avoid corrupting
  training data
- Add comment explaining global (not per-contact) RX time tracking
- Remove notifyListeners from retrain to avoid unnecessary widget rebuilds
- Run dart format
2026-03-14 17:32:08 -07:00

164 lines
5.1 KiB
Dart

import 'package:flutter/foundation.dart';
import 'package:flutter_test/flutter_test.dart';
import 'package:meshcore_open/models/delivery_observation.dart';
import 'package:meshcore_open/services/timeout_prediction_service.dart';
void main() {
late TimeoutPredictionService service;
setUp(() {
service = TimeoutPredictionService.noStorage();
});
test('trains on sample data and predicts sensible timeouts', () {
// Simulate realistic delivery data:
// Direct 0-hop messages: ~1500-2500ms
// 2-hop messages: ~4000-6000ms
// 4-hop messages: ~8000-12000ms
// Flood messages: ~3000-8000ms
final sampleData = [
// 0-hop direct
_obs(pathLength: 0, messageBytes: 20, deliveryMs: 1800),
_obs(pathLength: 0, messageBytes: 50, deliveryMs: 2100),
_obs(pathLength: 0, messageBytes: 80, deliveryMs: 2400),
_obs(pathLength: 0, messageBytes: 30, deliveryMs: 1925),
// 2-hop direct
_obs(pathLength: 2, messageBytes: 40, deliveryMs: 4500),
_obs(pathLength: 2, messageBytes: 60, deliveryMs: 5200),
_obs(pathLength: 2, messageBytes: 25, deliveryMs: 4100),
// 4-hop direct
_obs(pathLength: 4, messageBytes: 50, deliveryMs: 9800),
_obs(pathLength: 4, messageBytes: 30, deliveryMs: 8500),
_obs(pathLength: 4, messageBytes: 70, deliveryMs: 10570),
// Flood
_obs(pathLength: -1, messageBytes: 40, deliveryMs: 5000),
_obs(pathLength: -1, messageBytes: 60, deliveryMs: 6500),
];
// Feed all observations
for (final obs in sampleData) {
service.recordObservation(
contactKey: obs.contactKey,
pathLength: obs.pathLength,
messageBytes: obs.messageBytes,
tripTimeMs: obs.deliveryMs,
);
}
expect(service.hasModel, isTrue);
expect(service.observationCount, equals(12));
// Predict for different scenarios
final direct0 = service.predictTimeout(pathLength: 0, messageBytes: 50);
final direct2 = service.predictTimeout(pathLength: 2, messageBytes: 50);
final direct4 = service.predictTimeout(pathLength: 4, messageBytes: 50);
final flood = service.predictTimeout(pathLength: -1, messageBytes: 50);
// All should return non-null (model is trained)
expect(direct0, isNotNull);
expect(direct2, isNotNull);
expect(direct4, isNotNull);
expect(flood, isNotNull);
// More hops should predict longer timeouts
expect(direct4!, greaterThan(direct2!));
expect(direct2, greaterThan(direct0!));
// All should be positive
expect(direct0, greaterThan(0));
expect(direct4, greaterThan(0));
// Print predictions for visibility
debugPrint('Predictions (with 1.5x safety margin):');
debugPrint(' 0-hop direct: ${direct0}ms');
debugPrint(' 2-hop direct: ${direct2}ms');
debugPrint(' 4-hop direct: ${direct4}ms');
debugPrint(' flood: ${flood}ms');
});
test('returns null before minimum observations', () {
for (var i = 0; i < TimeoutPredictionService.minObservations - 1; i++) {
service.recordObservation(
contactKey: 'abc',
pathLength: 0,
messageBytes: 50,
tripTimeMs: 2000,
);
}
expect(service.hasModel, isFalse);
expect(service.predictTimeout(pathLength: 0, messageBytes: 50), isNull);
});
test('caps observations at maxObservations', () {
for (var i = 0; i < TimeoutPredictionService.maxObservations + 20; i++) {
service.recordObservation(
contactKey: 'abc',
pathLength: 0,
messageBytes: 50,
tripTimeMs: 2000 + i,
);
}
expect(
service.observationCount,
equals(TimeoutPredictionService.maxObservations),
);
});
test('blends per-contact stats after enough observations', () {
// Train with mixed contacts and varied features:
// contactA is fast (0-hop), contactB is slow (2-hop)
for (var i = 0; i < 12; i++) {
service.recordObservation(
contactKey: 'contactA',
pathLength: 0,
messageBytes: 30 + i,
tripTimeMs: 1500,
);
service.recordObservation(
contactKey: 'contactB',
pathLength: 2,
messageBytes: 30 + i,
tripTimeMs: 8000,
);
}
final predA = service.predictTimeout(
contactKey: 'contactA',
pathLength: 0,
messageBytes: 50,
);
final predB = service.predictTimeout(
contactKey: 'contactB',
pathLength: 0,
messageBytes: 50,
);
expect(predA, isNotNull);
expect(predB, isNotNull);
// Contact B (slow) should have a higher predicted timeout than A (fast)
expect(predB!, greaterThan(predA!));
debugPrint('Per-contact blending:');
debugPrint(' contactA (fast): ${predA}ms');
debugPrint(' contactB (slow): ${predB}ms');
});
}
DeliveryObservation _obs({
required int pathLength,
required int messageBytes,
required int deliveryMs,
String contactKey = 'test_contact',
}) {
return DeliveryObservation(
contactKey: contactKey,
pathLength: pathLength,
messageBytes: messageBytes,
secondsSinceLastRx: 5,
isFlood: pathLength < 0,
deliveryMs: deliveryMs,
timestamp: DateTime.now(),
);
}