infrastructure-scientific: Скилл для анализа и оптимизации

--- name: infrastructure-scientific description: Skill for the scientific infrastructure module providing numerical stability checks, performance benchmarking, scientific documentation generation, implementation validation, and module/workflow templates. Use when benchmarking functions, checking numerical stability, validating scientific implementations, or creating scientific module scaffolds. --- # Scientific Module Scientific computing utilities for research software development. ## Numerical Stability (`stability.py`) ```python from infrastructure.scientific import check_numerical_stability, StabilityTest # Check numerical stability of a function test = check_numerical_stability( func=my_computation, inputs=test_inputs, perturbation=1e-6, ) # Inspect results print(test.is_stable, test.max_deviation, test.condition_number) ``` ## Benchmarking (`benchmarking.py`) ```python from infrastructure.scientific import benchmark_function, BenchmarkResult, format_benchmark_report # Benchmark a function result = benchmark_function( func=my_algorithm, args=(data,), iterations=100, ) # Inspect results print(result.mean_time, result.std_time, result.min_time, result.max_time) # Generate performance report report = format_benchmark_report(results=[result]) ``` ## Scientific Documentation (`documentation.py`) ```python from infrastructure.scientific import generate_scientific_documentation, generate_api_documentation # Generate scientific documentation for a module docs = generate_scientific_documentation(module_path) # Generate API documentation api_docs = generate_api_documentation(module_path) ``` ## Implementation Validation (`validation.py`) ```python from infrastructure.scientific import ( validate_scientific_implementation, validate_scientific_best_practices, check_research_compliance, ) # Validate implementation against scientific standards issues = validate_scientific_implementation(source_dir) # Check best practices bp_issues = validate_scientific_best_practices(source_dir) # Check research compliance compliance = check_research_compliance(project_path) ``` ## Templates (`templates.py`) Generate scaffolding for new scientific modules and workflows: ```python from infrastructure.scientific import ( create_scientific_module_template, create_scientific_test_suite, create_scientific_workflow_template, ) # Create a new scientific module create_scientific_module_template( module_name="signal_processing", output_dir=project_src_dir, ) # Create matching test suite create_scientific_test_suite( module_name="signal_processing", output_dir=project_tests_dir, ) # Create a workflow template create_scientific_workflow_template( workflow_name="spectral_analysis", output_dir=project_scripts_dir, ) ```