quantrs2_core/realtime_monitoring/
functions.rs

1//! Auto-generated module
2//!
3//! 🤖 Generated with [SplitRS](https://github.com/cool-japan/splitrs)
4
5use crate::{
6    error::{QuantRS2Error, QuantRS2Result},
7    hardware_compilation::{HardwarePlatform, NativeGateType},
8    qubit::QubitId,
9};
10use std::{
11    collections::{HashMap, HashSet, VecDeque},
12    fmt,
13    sync::{Arc, RwLock},
14    thread,
15    time::{Duration, SystemTime},
16};
17
18use super::types::{
19    Alert, AlertLevel, AlertStatus, AlertThresholds, Anomaly, Correlation, DifficultyLevel,
20    ExpectedImprovement, ExportDestination, ExportFormat, ExportSettings, MetricMeasurement,
21    MetricType, MetricValue, MonitoringConfig, MonitoringStatus, OptimizationRecommendation,
22    PlatformMonitoringConfig, Prediction, RealtimeDataStore, RealtimeMonitor,
23    RecommendationPriority, RecommendationType, SuperconductingCollector, SystemStatus,
24    TrainingExample, TrendAnalysis, WidgetConfig, WidgetData,
25};
26
27/// Trait for platform-specific metric collection
28pub trait MetricCollector: std::fmt::Debug + Send + Sync {
29    /// Collect metrics from the platform
30    fn collect_metrics(&self) -> QuantRS2Result<Vec<MetricMeasurement>>;
31    /// Get supported metric types
32    fn supported_metrics(&self) -> HashSet<MetricType>;
33    /// Platform identifier
34    fn platform(&self) -> HardwarePlatform;
35    /// Initialize connection to hardware
36    fn initialize(&mut self) -> QuantRS2Result<()>;
37    /// Check connection status
38    fn is_connected(&self) -> bool;
39    /// Disconnect from hardware
40    fn disconnect(&mut self) -> QuantRS2Result<()>;
41}
42/// Trend analysis trait
43pub trait TrendAnalyzer: std::fmt::Debug + Send + Sync {
44    /// Analyze trend in metric data
45    fn analyze_trend(&self, data: &[MetricMeasurement]) -> QuantRS2Result<TrendAnalysis>;
46    /// Get analyzer name
47    fn name(&self) -> &str;
48}
49/// Anomaly detection trait
50pub trait AnomalyDetector: std::fmt::Debug + Send + Sync {
51    /// Detect anomalies in metric data
52    fn detect_anomalies(&self, data: &[MetricMeasurement]) -> QuantRS2Result<Vec<Anomaly>>;
53    /// Get detector name
54    fn name(&self) -> &str;
55    /// Get confidence threshold
56    fn confidence_threshold(&self) -> f64;
57}
58/// Correlation analysis trait
59pub trait CorrelationAnalyzer: std::fmt::Debug + Send + Sync {
60    /// Analyze correlations between metrics
61    fn analyze_correlations(
62        &self,
63        data: &HashMap<MetricType, Vec<MetricMeasurement>>,
64    ) -> QuantRS2Result<Vec<Correlation>>;
65    /// Get analyzer name
66    fn name(&self) -> &str;
67}
68/// Predictive modeling trait
69pub trait PredictiveModel: std::fmt::Debug + Send + Sync {
70    /// Predict future values
71    fn predict(
72        &self,
73        historical_data: &[MetricMeasurement],
74        horizon: Duration,
75    ) -> QuantRS2Result<Prediction>;
76    /// Update model with new data
77    fn update(&mut self, new_data: &[MetricMeasurement]) -> QuantRS2Result<()>;
78    /// Get model name
79    fn name(&self) -> &str;
80    /// Get model accuracy
81    fn accuracy(&self) -> f64;
82}
83/// Alert handler trait
84pub trait AlertHandler: std::fmt::Debug + Send + Sync {
85    /// Handle an alert
86    fn handle_alert(&self, alert: &Alert) -> QuantRS2Result<()>;
87    /// Get handler name
88    fn name(&self) -> &str;
89    /// Check if handler can handle this alert level
90    fn can_handle(&self, level: AlertLevel) -> bool;
91}
92/// Optimization strategy trait
93pub trait OptimizationStrategy: std::fmt::Debug + Send + Sync {
94    /// Analyze performance data and generate recommendations
95    fn analyze(&self, data: &RealtimeDataStore) -> QuantRS2Result<Vec<OptimizationRecommendation>>;
96    /// Get strategy name
97    fn name(&self) -> &str;
98    /// Get strategy priority
99    fn priority(&self) -> u32;
100}
101/// Machine learning model trait
102pub trait MLModel: std::fmt::Debug + Send + Sync {
103    /// Train model with historical data
104    fn train(&mut self, training_data: &[TrainingExample]) -> QuantRS2Result<()>;
105    /// Predict recommendations
106    fn predict(
107        &self,
108        input_data: &[MetricMeasurement],
109    ) -> QuantRS2Result<Vec<OptimizationRecommendation>>;
110    /// Get model accuracy
111    fn accuracy(&self) -> f64;
112    /// Get model name
113    fn name(&self) -> &str;
114}
115/// Dashboard widget trait
116pub trait DashboardWidget: std::fmt::Debug + Send + Sync {
117    /// Render widget with current data
118    fn render(&self, data: &RealtimeDataStore) -> QuantRS2Result<WidgetData>;
119    /// Get widget configuration
120    fn get_config(&self) -> WidgetConfig;
121    /// Update widget configuration
122    fn update_config(&mut self, config: WidgetConfig) -> QuantRS2Result<()>;
123}
124/// Data exporter trait
125pub trait DataExporter: std::fmt::Debug + Send + Sync {
126    /// Export data in specific format
127    fn export(
128        &self,
129        data: &[MetricMeasurement],
130        destination: &ExportDestination,
131    ) -> QuantRS2Result<()>;
132    /// Get supported format
133    fn format(&self) -> ExportFormat;
134    /// Validate export configuration
135    fn validate_config(&self, destination: &ExportDestination) -> QuantRS2Result<()>;
136}
137#[cfg(test)]
138mod tests {
139    use super::*;
140    #[test]
141    fn test_realtime_monitor_creation() {
142        let config = MonitoringConfig::default();
143        let monitor = RealtimeMonitor::new(config);
144        assert!(monitor.is_ok());
145    }
146    #[test]
147    fn test_metric_measurement() {
148        let measurement = MetricMeasurement {
149            metric_type: MetricType::GateErrorRate,
150            value: MetricValue::Float(0.001),
151            timestamp: SystemTime::now(),
152            qubit: Some(QubitId::new(0)),
153            gate_type: Some(NativeGateType::CNOT),
154            metadata: HashMap::new(),
155            uncertainty: Some(0.0001),
156        };
157        assert_eq!(measurement.metric_type, MetricType::GateErrorRate);
158        assert!(matches!(measurement.value, MetricValue::Float(0.001)));
159    }
160    #[test]
161    fn test_superconducting_collector() {
162        let config = PlatformMonitoringConfig {
163            platform: HardwarePlatform::Superconducting,
164            monitored_metrics: HashSet::new(),
165            sampling_rates: HashMap::new(),
166            custom_thresholds: HashMap::new(),
167            connection_settings: HashMap::new(),
168        };
169        let mut collector = SuperconductingCollector::new(config);
170        assert_eq!(collector.platform(), HardwarePlatform::Superconducting);
171        assert!(!collector.is_connected());
172        assert!(collector.initialize().is_ok());
173        assert!(collector.is_connected());
174        let metrics = collector.collect_metrics();
175        assert!(metrics.is_ok());
176        assert!(!metrics
177            .expect("Metrics collection should succeed")
178            .is_empty());
179    }
180    #[test]
181    fn test_data_store() {
182        let mut store = RealtimeDataStore::new(Duration::from_secs(3600));
183        let measurement = MetricMeasurement {
184            metric_type: MetricType::GateErrorRate,
185            value: MetricValue::Float(0.001),
186            timestamp: SystemTime::now(),
187            qubit: None,
188            gate_type: None,
189            metadata: HashMap::new(),
190            uncertainty: None,
191        };
192        store.add_measurement(measurement);
193        assert!(store.time_series.contains_key(&MetricType::GateErrorRate));
194        assert!(store
195            .aggregated_stats
196            .contains_key(&MetricType::GateErrorRate));
197        let stats = store
198            .aggregated_stats
199            .get(&MetricType::GateErrorRate)
200            .expect("GateErrorRate stats should exist after adding measurement");
201        assert_eq!(stats.sample_count, 1);
202        assert_eq!(stats.mean, 0.001);
203    }
204    #[test]
205    fn test_alert_creation() {
206        let alert = Alert {
207            id: "test_alert".to_string(),
208            level: AlertLevel::Warning,
209            message: "Test alert message".to_string(),
210            affected_metrics: vec![MetricType::GateErrorRate],
211            timestamp: SystemTime::now(),
212            source: "test".to_string(),
213            suggested_actions: vec!["Check calibration".to_string()],
214            status: AlertStatus::Active,
215        };
216        assert_eq!(alert.level, AlertLevel::Warning);
217        assert_eq!(alert.status, AlertStatus::Active);
218        assert!(alert.affected_metrics.contains(&MetricType::GateErrorRate));
219    }
220    #[test]
221    fn test_monitoring_config() {
222        let config = MonitoringConfig::default();
223        assert_eq!(config.monitoring_interval, Duration::from_secs(1));
224        assert_eq!(config.data_retention_period, Duration::from_secs(24 * 3600));
225        assert!(!config.export_settings.enable_export);
226    }
227    #[test]
228    fn test_metric_value_types() {
229        let float_value = MetricValue::Float(1.23);
230        let int_value = MetricValue::Integer(42);
231        let bool_value = MetricValue::Boolean(true);
232        let duration_value = MetricValue::Duration(Duration::from_millis(100));
233        assert!(matches!(float_value, MetricValue::Float(1.23)));
234        assert!(matches!(int_value, MetricValue::Integer(42)));
235        assert!(matches!(bool_value, MetricValue::Boolean(true)));
236        assert!(matches!(duration_value, MetricValue::Duration(_)));
237    }
238    #[test]
239    fn test_alert_thresholds() {
240        let thresholds = AlertThresholds::default();
241        assert_eq!(thresholds.max_gate_error_rate, 0.01);
242        assert_eq!(thresholds.max_readout_error_rate, 0.05);
243        assert_eq!(thresholds.min_coherence_time, Duration::from_micros(50));
244    }
245    #[test]
246    fn test_optimization_recommendation() {
247        let recommendation = OptimizationRecommendation {
248            id: "test_rec".to_string(),
249            recommendation_type: RecommendationType::GateOptimization,
250            description: "Optimize gate sequence".to_string(),
251            affected_components: vec!["qubit_0".to_string()],
252            expected_improvement: ExpectedImprovement {
253                fidelity_improvement: Some(0.001),
254                speed_improvement: Some(0.1),
255                error_rate_reduction: Some(0.0005),
256                resource_savings: None,
257            },
258            implementation_difficulty: DifficultyLevel::Medium,
259            priority: RecommendationPriority::High,
260            timestamp: SystemTime::now(),
261        };
262        assert_eq!(
263            recommendation.recommendation_type,
264            RecommendationType::GateOptimization
265        );
266        assert_eq!(
267            recommendation.implementation_difficulty,
268            DifficultyLevel::Medium
269        );
270        assert_eq!(recommendation.priority, RecommendationPriority::High);
271    }
272    #[test]
273    fn test_export_settings() {
274        let settings = ExportSettings {
275            enable_export: true,
276            export_formats: vec![ExportFormat::JSON, ExportFormat::CSV],
277            export_destinations: vec![],
278            export_frequency: Duration::from_secs(1800),
279            compression_enabled: true,
280        };
281        assert!(settings.enable_export);
282        assert_eq!(settings.export_formats.len(), 2);
283        assert!(settings.compression_enabled);
284    }
285    #[test]
286    fn test_monitoring_status() {
287        let status = MonitoringStatus::new();
288        assert_eq!(status.overall_status, SystemStatus::Offline);
289        assert_eq!(status.active_collectors, 0);
290        assert_eq!(status.total_data_points, 0);
291    }
292}
quantrs2_core/realtime_monitoring/functions.rs

quantrs2_core/realtime_monitoring/
functions.rs
