rustorch 0.6.29

Production-ready PyTorch-compatible deep learning library in Rust with special mathematical functions (gamma, Bessel, error functions), statistical distributions, Fourier transforms (FFT/RFFT), matrix decomposition (SVD/QR/LU/eigenvalue), automatic differentiation, neural networks, computer vision transforms, complete GPU acceleration (CUDA/Metal/OpenCL), SIMD optimizations, parallel processing, WebAssembly browser support, comprehensive distributed learning support, and performance validation
Documentation
//! Data Validation & Quality Assurance Framework (Phase 1 Component 6)
//! データ検証・品質保証フレームワーク(フェーズ1コンポーネント6)
//!
//! Enterprise-grade data validation and quality assurance system with:
//! - Real-time tensor data validation and quality assessment
//! - Statistical anomaly detection and outlier identification
//! - Schema validation and data consistency checking
//! - Quality metrics collection and trend analysis
//! - Integration with profiling system for performance monitoring
//! - Automated data cleaning and repair suggestions
//!
//! エンタープライズグレードのデータ検証・品質保証システム:
//! - リアルタイムテンソルデータ検証と品質評価
//! - 統計的異常検出と外れ値識別
//! - スキーマ検証とデータ整合性チェック
//! - 品質メトリクス収集とトレンド分析
//! - パフォーマンス監視のためのプロファイリング統合
//! - 自動データクリーニングと修復提案

use crate::error::{RusTorchError, RusTorchResult};
use std::collections::HashMap;
use std::fmt;
use std::sync::{Arc, Mutex};
use std::time::{Duration, Instant};

// Core validation modules
pub mod anomaly_detector;
pub mod consistency_checker;
pub mod core;
pub mod quality_metrics;
pub mod quality_reporter;
pub mod real_time_validator;

// Enhanced re-exports for the validation system
pub use anomaly_detector::{
    AnomalyConfiguration, AnomalyDetector, AnomalyResult, AnomalyType, OutlierDetection,
    StatisticalMethod,
};
pub use consistency_checker::{
    ConsistencyChecker, ConsistencyResult, ConsistencyRule, DataConsistency, ReferentialIntegrity,
};
pub use core::{
    DataSchema, SchemaValidation, ValidationConfig, ValidationEngine, ValidationLevel,
    ValidationResult, ValidationRule,
};
pub use quality_metrics::{
    DataQualityAssessment, MetricThresholds, QualityDimension, QualityMetrics, QualityScore,
    QualityTrend,
};
pub use quality_reporter::{
    QualityDashboard, QualityReport, QualityReporter, ReportConfiguration, ReportFormat,
};
pub use real_time_validator::{
    RealTimeConfig, RealTimeValidator, StreamingValidation, ValidationBuffer, ValidationStream,
};

/// Main validation framework orchestrator
/// メイン検証フレームワークオーケストレーター
#[derive(Debug)]
pub struct DataValidationFramework {
    /// Core validation engine
    /// コア検証エンジン
    validation_engine: ValidationEngine,
    /// Quality metrics system
    /// 品質メトリクスシステム
    quality_metrics: QualityMetrics,
    /// Anomaly detection system
    /// 異常検出システム
    anomaly_detector: AnomalyDetector,
    /// Consistency checker
    /// 整合性チェッカー
    consistency_checker: ConsistencyChecker,
    /// Real-time validator
    /// リアルタイム検証
    real_time_validator: Option<RealTimeValidator>,
    /// Quality reporter
    /// 品質レポーター
    quality_reporter: QualityReporter,
    /// Framework configuration
    /// フレームワーク設定
    config: FrameworkConfig,
}

/// Framework configuration
/// フレームワーク設定
#[derive(Debug, Clone)]
pub struct FrameworkConfig {
    /// Enable real-time validation
    /// リアルタイム検証を有効化
    pub enable_real_time: bool,
    /// Validation performance budget (microseconds)
    /// 検証パフォーマンス予算(マイクロ秒)
    pub performance_budget_us: u64,
    /// Quality score threshold for alerts
    /// アラート用品質スコア閾値
    pub quality_threshold: f64,
    /// Enable anomaly detection
    /// 異常検出を有効化
    pub enable_anomaly_detection: bool,
    /// Enable automatic reporting
    /// 自動レポート生成を有効化
    pub enable_auto_reporting: bool,
}

impl Default for FrameworkConfig {
    fn default() -> Self {
        Self {
            enable_real_time: true,
            performance_budget_us: 1000, // 1ms budget
            quality_threshold: 0.8,      // 80% quality threshold
            enable_anomaly_detection: true,
            enable_auto_reporting: true,
        }
    }
}

impl DataValidationFramework {
    /// Create new data validation framework
    /// 新しいデータ検証フレームワークを作成
    pub fn new(config: FrameworkConfig) -> RusTorchResult<Self> {
        let validation_engine = ValidationEngine::new(ValidationConfig::default())?;
        let quality_metrics = QualityMetrics::new();
        let anomaly_detector = AnomalyDetector::new(AnomalyConfiguration::default());
        let consistency_checker = ConsistencyChecker::new();
        let quality_reporter = QualityReporter::new(ReportConfiguration::default());

        let real_time_validator = if config.enable_real_time {
            Some(RealTimeValidator::new(RealTimeConfig::default())?)
        } else {
            None
        };

        Ok(Self {
            validation_engine,
            quality_metrics,
            anomaly_detector,
            consistency_checker,
            real_time_validator,
            quality_reporter,
            config,
        })
    }

    /// Validate tensor data comprehensively
    /// テンソルデータを包括的に検証
    pub fn validate_tensor_data<T>(
        &mut self,
        tensor: &crate::tensor::Tensor<T>,
    ) -> RusTorchResult<ValidationSummary>
    where
        T: num_traits::Float + std::fmt::Debug + Clone + Send + Sync + 'static,
    {
        let start_time = Instant::now();

        // 1. Basic validation
        let validation_result = self.validation_engine.validate_tensor(tensor)?;

        // 2. Quality assessment
        let quality_assessment = self.quality_metrics.assess_quality(tensor)?;

        // 3. Anomaly detection
        let anomaly_result = if self.config.enable_anomaly_detection {
            Some(self.anomaly_detector.detect_anomalies(tensor)?)
        } else {
            None
        };

        // 4. Consistency check
        let consistency_result = self.consistency_checker.check_consistency(tensor)?;

        // 5. Performance validation
        let validation_time = start_time.elapsed();
        if validation_time.as_micros() as u64 > self.config.performance_budget_us {
            println!(
                "⚠️ Validation exceeded performance budget: {}μs > {}μs",
                validation_time.as_micros(),
                self.config.performance_budget_us
            );
        }

        // 6. Create summary
        let summary = ValidationSummary {
            validation_result,
            quality_assessment: quality_assessment.clone(),
            anomaly_result,
            consistency_result,
            validation_time,
            overall_quality_score: quality_assessment.overall_score,
            passed: quality_assessment.overall_score >= self.config.quality_threshold,
        };

        // 7. Generate report if enabled
        if self.config.enable_auto_reporting {
            self.quality_reporter.add_validation_result(&summary)?;
        }

        Ok(summary)
    }

    /// Start real-time validation monitoring
    /// リアルタイム検証監視を開始
    pub fn start_real_time_monitoring(&mut self) -> RusTorchResult<()> {
        if let Some(validator) = &mut self.real_time_validator {
            validator.start_monitoring()?;
            println!("🔍 Real-time data validation monitoring started");
        }
        Ok(())
    }

    /// Stop real-time validation monitoring
    /// リアルタイム検証監視を停止
    pub fn stop_real_time_monitoring(&mut self) -> RusTorchResult<()> {
        if let Some(validator) = &mut self.real_time_validator {
            validator.stop_monitoring()?;
            println!("🔍 Real-time data validation monitoring stopped");
        }
        Ok(())
    }

    /// Generate comprehensive quality report
    /// 包括的品質レポートを生成
    pub fn generate_quality_report(&self, format: ReportFormat) -> RusTorchResult<String> {
        self.quality_reporter.generate_report(format)
    }

    /// Get framework statistics
    /// フレームワーク統計を取得
    pub fn get_statistics(&self) -> FrameworkStatistics {
        FrameworkStatistics {
            total_validations: self.quality_reporter.get_validation_count(),
            average_quality_score: self.quality_reporter.get_average_quality_score(),
            anomalies_detected: self.anomaly_detector.get_anomaly_count(),
            consistency_violations: self.consistency_checker.get_violation_count(),
            uptime: self.quality_reporter.get_uptime(),
        }
    }
}

/// Framework statistics
/// フレームワーク統計
#[derive(Debug, Clone)]
pub struct FrameworkStatistics {
    /// Total number of validations performed
    /// 実行された検証の総数
    pub total_validations: usize,
    /// Average quality score across all validations
    /// 全検証の平均品質スコア
    pub average_quality_score: f64,
    /// Number of anomalies detected
    /// 検出された異常数
    pub anomalies_detected: usize,
    /// Number of consistency violations found
    /// 発見された整合性違反数
    pub consistency_violations: usize,
    /// Framework uptime
    /// フレームワーク稼働時間
    pub uptime: Duration,
}

impl fmt::Display for FrameworkStatistics {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        write!(
            f,
            "📊 Data Validation Framework Statistics\n\
             =====================================\n\
             Total Validations: {}\n\
             Average Quality Score: {:.2}\n\
             Anomalies Detected: {}\n\
             Consistency Violations: {}\n\
             Uptime: {:.2}s",
            self.total_validations,
            self.average_quality_score,
            self.anomalies_detected,
            self.consistency_violations,
            self.uptime.as_secs_f64()
        )
    }
}

/// Validation summary for comprehensive results
/// 包括的結果のための検証サマリー
#[derive(Debug, Clone)]
pub struct ValidationSummary {
    /// Basic validation result
    /// 基本検証結果
    pub validation_result: ValidationResult,
    /// Quality assessment
    /// 品質評価
    pub quality_assessment: DataQualityAssessment,
    /// Anomaly detection result (optional)
    /// 異常検出結果(オプション)
    pub anomaly_result: Option<AnomalyResult>,
    /// Consistency check result
    /// 整合性チェック結果
    pub consistency_result: ConsistencyResult,
    /// Time taken for validation
    /// 検証にかかった時間
    pub validation_time: Duration,
    /// Overall quality score
    /// 総合品質スコア
    pub overall_quality_score: f64,
    /// Whether validation passed
    /// 検証が合格したか
    pub passed: bool,
}

impl fmt::Display for ValidationSummary {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        let status = if self.passed {
            "✅ PASSED"
        } else {
            "❌ FAILED"
        };
        write!(
            f,
            "🔍 Data Validation Summary\n\
             ========================\n\
             Status: {}\n\
             Overall Quality Score: {:.2}\n\
             Validation Time: {:.3}ms\n\
             Basic Validation: {}\n\
             Quality Assessment: {:.2} ({})\n\
             Anomalies: {}\n\
             Consistency: {}",
            status,
            self.overall_quality_score,
            self.validation_time.as_secs_f64() * 1000.0,
            if self.validation_result.is_valid {
                ""
            } else {
                ""
            },
            self.quality_assessment.overall_score,
            self.quality_assessment.quality_grade(),
            if let Some(ref anomaly) = self.anomaly_result {
                if anomaly.anomalies_found > 0 {
                    format!("{} detected", anomaly.anomalies_found)
                } else {
                    "None".to_string()
                }
            } else {
                "Disabled".to_string()
            },
            if self.consistency_result.is_consistent {
                ""
            } else {
                ""
            }
        )
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_framework_creation() {
        let config = FrameworkConfig::default();
        let result = DataValidationFramework::new(config);
        assert!(result.is_ok());
    }

    #[test]
    fn test_framework_config_default() {
        let config = FrameworkConfig::default();
        assert!(config.enable_real_time);
        assert_eq!(config.performance_budget_us, 1000);
        assert_eq!(config.quality_threshold, 0.8);
        assert!(config.enable_anomaly_detection);
        assert!(config.enable_auto_reporting);
    }
}