# Service Layer and Infrastructure

This diagram shows the service layer components that provide infrastructure support for the core simulation and analysis.

```{mermaid}
classDiagram
    %% Batch Processing Services
    class BatchProcessor {
        -config: BatchConfig
        -executor: ParallelExecutor
        -cache: SmartCache
        -progress_monitor: ProgressMonitor
        +process_scenarios(scenarios: List) BatchResults
        +process_parameter_sweep(params: dict) SweepResults
        +process_convergence_study() ConvergenceResults
        +resume_from_checkpoint(checkpoint_id: str)
    }

    class ParallelExecutor {
        -n_workers: int
        -chunk_size: int
        -backend: str
        -memory_limit: float
        +map(func: Callable, items: List) List
        +map_reduce(map_func, reduce_func, items) Any
        +scatter_gather(tasks: List) List
        +get_worker_status() dict
    }

    class SmartCache {
        -cache_dir: Path
        -max_size_gb: float
        -ttl_hours: int
        -compression: bool
        +get(key: str) Optional[Any]
        +set(key: str, value: Any)
        +invalidate(pattern: str)
        +get_stats() CacheStats
    }

    %% Progress and Monitoring
    class ProgressMonitor {
        -total_tasks: int
        -completed_tasks: int
        -start_time: float
        -update_interval: float
        +update(progress: float, message: str)
        +estimate_time_remaining() float
        +get_throughput() float
        +display_progress_bar()
    }

    class ConvergenceMonitor {
        -metrics: List[float]
        -threshold: float
        -window_size: int
        -patience: int
        +add_metric(value: float)
        +check_convergence() bool
        +get_convergence_rate() float
        +plot_convergence_history()
    }

    %% Trajectory Storage
    class TrajectoryStorage {
        -storage_backend: str
        -compression_level: int
        -chunk_size: int
        +store_trajectory(sim_id: str, data: ndarray)
        +load_trajectory(sim_id: str) ndarray
        +store_batch(trajectories: dict)
        +query_trajectories(filter: dict) List
        +get_storage_stats() dict
    }

    %% Parameter Management
    class ParameterSweep {
        -base_params: dict
        -sweep_params: dict
        -sweep_type: str
        -n_points: int
        +generate_grid() List[dict]
        +generate_latin_hypercube() List[dict]
        +generate_sobol_sequence() List[dict]
        +adaptive_sampling(results: List) List[dict]
    }

    class ScenarioManager {
        -scenarios: Dict[str, Scenario]
        -active_scenario: str
        +add_scenario(name: str, params: dict)
        +load_scenario(name: str) Scenario
        +compare_scenarios(names: List[str]) ComparisonResults
        +export_scenarios(path: str)
    }

    %% Performance Optimization
    class PerformanceOptimizer {
        -profiler: cProfile
        -memory_profiler: MemoryProfiler
        -optimization_level: int
        +profile_function(func: Callable) ProfileResult
        +optimize_memory_usage()
        +enable_numba_jit()
        +vectorize_operations()
        +get_bottlenecks() List[Bottleneck]
    }

    class VectorizedOperations {
        <<static>>
        +calculate_returns(prices: ndarray) ndarray
        +calculate_drawdowns(equity: ndarray) ndarray
        +calculate_rolling_stats(data: ndarray, window: int) dict
        +apply_vectorized_claim(claims: ndarray, limits: ndarray) ndarray
    }

    %% Benchmarking
    class BenchmarkSuite {
        -benchmarks: List[Benchmark]
        -baseline_results: dict
        -comparison_results: dict
        +add_benchmark(benchmark: Benchmark)
        +run_all_benchmarks() BenchmarkResults
        +compare_implementations(impl1, impl2) ComparisonReport
        +generate_performance_report() str
    }

    class Benchmark {
        +name: str
        +setup_func: Callable
        +test_func: Callable
        +teardown_func: Callable
        +n_iterations: int
        +run() BenchmarkResult
    }

    %% Validation Services
    class AccuracyValidator {
        -tolerance: float
        -reference_impl: ReferenceImplementations
        +validate_calculation(func, inputs, expected) bool
        +validate_convergence(results: List) bool
        +validate_edge_cases() ValidationReport
        +cross_validate(method1, method2) float
    }

    class StrategyBacktester {
        -historical_data: DataFrame
        -strategy: InsuranceStrategy
        -metrics: List[str]
        +backtest(start_date, end_date) BacktestResults
        +walk_forward_analysis(window_size: int) WalkForwardResults
        +calculate_performance_metrics() dict
        +generate_backtest_report() str
    }

    %% Reporting Services
    class ExcelReporter {
        -template_path: str
        -output_path: str
        -workbook: Workbook
        +create_summary_sheet(results: dict)
        +create_charts(data: DataFrame)
        +add_sensitivity_tables(sensitivity: SensitivityResult)
        +add_risk_metrics(metrics: RiskMetrics)
        +format_report()
        +save()
    }

    class ResultAggregator {
        -results: List[SimulationResults]
        -aggregation_funcs: dict
        +add_results(results: SimulationResults)
        +calculate_statistics() SummaryStatistics
        +calculate_percentiles(percentiles: List) dict
        +group_by(key: str) Dict[str, List]
        +export_aggregated_data(format: str)
    }

    %% Visualization Services
    class FigureFactory {
        -style_manager: StyleManager
        -default_size: tuple
        -dpi: int
        +create_line_plot(data: DataFrame) Figure
        +create_distribution_plot(data: ndarray) Figure
        +create_heatmap(data: ndarray) Figure
        +create_dashboard(results: dict) Figure
        +save_figure(fig: Figure, path: str)
    }

    class StyleManager {
        -theme: Theme
        -color_palette: List[str]
        -font_settings: dict
        +apply_theme(theme: Theme)
        +get_color_cycle() List
        +format_axis(ax: Axes)
        +add_annotations(ax: Axes, annotations: List)
    }

    %% Relationships
    BatchProcessor --> ParallelExecutor : uses
    BatchProcessor --> SmartCache : caches with
    BatchProcessor --> ProgressMonitor : monitors with

    ParallelExecutor --> VectorizedOperations : optimizes with

    ParameterSweep --> ScenarioManager : generates for

    PerformanceOptimizer --> VectorizedOperations : creates
    PerformanceOptimizer --> BenchmarkSuite : benchmarks with

    BenchmarkSuite --> Benchmark : runs

    AccuracyValidator --> StrategyBacktester : validates

    ResultAggregator --> ExcelReporter : feeds
    ResultAggregator --> FigureFactory : visualizes with

    FigureFactory --> StyleManager : styled by

    BatchProcessor --> TrajectoryStorage : stores in
    ConvergenceMonitor --> ProgressMonitor : reports to
```

## Service Interaction Flow

```{mermaid}
sequenceDiagram
    participant Client
    participant BP as BatchProcessor
    participant PE as ParallelExecutor
    participant SC as SmartCache
    participant TS as TrajectoryStorage
    participant PM as ProgressMonitor
    participant RA as ResultAggregator
    participant ER as ExcelReporter

    Client->>BP: Submit batch job
    BP->>SC: Check cache
    alt Cache hit
        SC-->>BP: Cached results
        BP-->>Client: Return results
    else Cache miss
        BP->>PM: Initialize monitor
        BP->>PE: Distribute work

        loop Parallel execution
            PE->>PE: Process chunk
            PE->>PM: Update progress
            PM-->>Client: Progress update
        end

        PE-->>BP: Raw results
        BP->>TS: Store trajectories
        BP->>SC: Cache results
        BP->>RA: Aggregate results
        RA->>ER: Generate report
        ER-->>Client: Excel report
        BP-->>Client: Complete results
    end
```

## Service Layer Patterns

### 1. **Service Locator Pattern**
- Central registry for service discovery
- Dynamic service binding at runtime

### 2. **Repository Pattern**
- TrajectoryStorage abstracts data persistence
- ScenarioManager provides scenario repository

### 3. **Unit of Work Pattern**
- BatchProcessor coordinates complex operations
- Ensures consistency across service calls

### 4. **Pipeline Pattern**
- Data flows through processing pipeline
- Each service transforms data for next stage

### 5. **Decorator Pattern**
- ProgressMonitor decorates long-running operations
- SmartCache decorates expensive computations

### 6. **Adapter Pattern**
- ExcelReporter adapts results to Excel format
- Different storage backends adapted by TrajectoryStorage