Crate datasynth_eval 

Synthetic Data Evaluation Framework

This crate provides comprehensive evaluation capabilities for validating the quality and correctness of generated synthetic financial data.

Features

• Statistical Quality: Benford’s Law, amount distributions, line item patterns
• Semantic Coherence: Balance sheet validation, subledger reconciliation
• Data Quality: Uniqueness, completeness, format consistency
• ML-Readiness: Feature distributions, label quality, graph structure
• Reporting: HTML and JSON reports with pass/fail thresholds

Example

use datasynth_eval::{Evaluator, EvaluationConfig};

let config = EvaluationConfig::default();
let evaluator = Evaluator::new(config);

// Evaluate generated data
let result = evaluator.evaluate(&generation_result)?;

// Generate report
result.generate_html_report("evaluation_report.html")?;

Re-exports

pub use config::EvaluationConfig;

pub use config::EvaluationThresholds;

pub use error::EvalError;

pub use error::EvalResult;

pub use statistical::AmountDistributionAnalysis;

pub use statistical::AmountDistributionAnalyzer;

pub use statistical::BenfordAnalysis;

pub use statistical::BenfordAnalyzer;

pub use statistical::BenfordConformity;

pub use statistical::LineItemAnalysis;

pub use statistical::LineItemAnalyzer;

pub use statistical::LineItemEntry;

pub use statistical::StatisticalEvaluation;

pub use statistical::TemporalAnalysis;

pub use statistical::TemporalAnalyzer;

pub use statistical::TemporalEntry;

pub use coherence::AuditTrailEvaluation;

pub use coherence::AuditTrailGap;

pub use coherence::BalanceSheetEvaluation;

pub use coherence::BalanceSheetEvaluator;

pub use coherence::CoherenceEvaluation;

pub use coherence::DocumentChainEvaluation;

pub use coherence::DocumentChainEvaluator;

pub use coherence::FairValueEvaluation;

pub use coherence::FrameworkViolation;

pub use coherence::ICMatchingEvaluation;

pub use coherence::ICMatchingEvaluator;

pub use coherence::ImpairmentEvaluation;

pub use coherence::IsaComplianceEvaluation;

pub use coherence::LeaseAccountingEvaluation;

pub use coherence::LeaseAccountingEvaluator;

pub use coherence::LeaseEvaluation;

pub use coherence::PcaobComplianceEvaluation;

pub use coherence::PerformanceObligation;

pub use coherence::ReferentialIntegrityEvaluation;

pub use coherence::ReferentialIntegrityEvaluator;

pub use coherence::RevenueContract;

pub use coherence::RevenueRecognitionEvaluation;

pub use coherence::RevenueRecognitionEvaluator;

pub use coherence::SoxComplianceEvaluation;

pub use coherence::StandardsComplianceEvaluation;

pub use coherence::StandardsThresholds;

pub use coherence::SubledgerEvaluator;

pub use coherence::SubledgerReconciliationEvaluation;

pub use coherence::VariableConsideration;

pub use coherence::ViolationSeverity;

pub use quality::CompletenessAnalysis;

pub use quality::CompletenessAnalyzer;

pub use quality::ConsistencyAnalysis;

pub use quality::ConsistencyAnalyzer;

pub use quality::ConsistencyRule;

pub use quality::DuplicateInfo;

pub use quality::FieldCompleteness;

pub use quality::FormatAnalysis;

pub use quality::FormatAnalyzer;

pub use quality::FormatVariation;

pub use quality::QualityEvaluation;

pub use quality::UniquenessAnalysis;

pub use quality::UniquenessAnalyzer;

pub use ml::FeatureAnalysis;

pub use ml::FeatureAnalyzer;

pub use ml::FeatureStats;

pub use ml::GraphAnalysis;

pub use ml::GraphAnalyzer;

pub use ml::GraphMetrics;

pub use ml::LabelAnalysis;

pub use ml::LabelAnalyzer;

pub use ml::LabelDistribution;

pub use ml::MLReadinessEvaluation;

pub use ml::SplitAnalysis;

pub use ml::SplitAnalyzer;

pub use ml::SplitMetrics;

pub use report::BaselineComparison;

pub use report::ComparisonResult;

pub use report::EvaluationReport;

pub use report::HtmlReportGenerator;

pub use report::JsonReportGenerator;

pub use report::MetricChange;

pub use report::ReportMetadata;

pub use report::ThresholdChecker;

pub use report::ThresholdResult;

pub use tuning::ConfigSuggestion;

pub use tuning::ConfigSuggestionGenerator;

pub use tuning::TuningAnalyzer;

pub use tuning::TuningCategory;

pub use tuning::TuningOpportunity;

pub use enhancement::AutoTuneResult;

pub use enhancement::AutoTuner;

pub use enhancement::ConfigPatch;

pub use enhancement::EnhancementReport;

pub use enhancement::Recommendation;

pub use enhancement::RecommendationCategory;

pub use enhancement::RecommendationEngine;

pub use enhancement::RecommendationPriority;

pub use enhancement::RootCause;

pub use enhancement::SuggestedAction;

pub use benchmarks::all_benchmarks;

pub use benchmarks::anomaly_bench_1k;

pub use benchmarks::data_quality_100k;

pub use benchmarks::entity_match_5k;

pub use benchmarks::fraud_detect_10k;

pub use benchmarks::get_benchmark;

pub use benchmarks::graph_fraud_10k;

pub use benchmarks::BaselineModelType;

pub use benchmarks::BaselineResult;

pub use benchmarks::BenchmarkBuilder;

pub use benchmarks::BenchmarkSuite;

pub use benchmarks::BenchmarkTaskType;

pub use benchmarks::CostMatrix;

pub use benchmarks::DatasetSpec;

pub use benchmarks::EvaluationSpec;

pub use benchmarks::FeatureSet;

pub use benchmarks::LeaderboardEntry;

pub use benchmarks::MetricType;

pub use benchmarks::SplitRatios;

Modules

benchmarks

Benchmark suite definitions for ML evaluation.

coherence

Semantic coherence evaluation module.

config

Configuration for the evaluation framework.

enhancement

Enhancement derivation module for automatic configuration optimization.

error

Error types for the evaluation framework.

ml

ML-readiness evaluation module.

quality

Data quality evaluation module.

report

Report generation module.

statistical

Statistical quality evaluation module.

tuning

Configuration tuning and optimization suggestions.

Structs

ComprehensiveEvaluation

Comprehensive evaluation result combining all evaluation modules.

Evaluator

Main evaluator that coordinates all evaluation modules.