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…ualify AbstractOptimizationSolver references
- Implement AbstractStrategy contract with type-level and instance-level methods - Add StrategyMetadata for option specifications with validation - Create StrategyRegistry for explicit dependency management - Provide strategy builders and configuration utilities - Include introspection API for metadata and option access - Add comprehensive test suite (423 tests passing) - Follow CTModels.jl patterns for consistency Features: - Two-level contract (type metadata + instance configuration) - Immutable registry pattern for strategy lookup - Option provenance tracking (user/default/computed) - Alias resolution and suggestion utilities - Full validation pipeline with detailed error messages
- Implement smart option routing with disambiguation support - Add strategy-to-family mapping and option ownership detection - Provide method-based strategy builders and introspection wrappers - Support single and multi-strategy disambiguation syntax - Include comprehensive test suite (79 tests passing) Features: - route_all_options() - main routing function with auto-routing - extract_strategy_ids() - disambiguation syntax detection - build_strategy_to_family_map() - strategy family mapping - build_option_ownership_map() - option ownership detection - build_strategy_from_method() - convenience strategy builders - Detailed error messages with actionable suggestions Disambiguation syntax: - Single: backend = (:sparse, :adnlp) - Multi: backend = ((:sparse, :adnlp), (:cpu, :ipopt)) - Auto-routing for unambiguous options
- Implement AbstractOptimizationProblem contract with builder interface - Add concrete builder types for ADNLPModels and ExaModels backends - Provide model and solution building functions (build_model, build_solution) - Include solver info extraction utilities (extract_solver_infos) - Add comprehensive test suite (139 tests passing) - Update MadNLP extension with solver info extraction - Migrate test problems from CTModels to CTSolvers Features: - AbstractOptimizationProblem contract with 4 required builder methods - ADNLPModelBuilder and ExaModelBuilder callable builders - ADNLPSolutionBuilder and ExaSolutionBuilder for solution conversion - Type-stable builder patterns with proper error handling - Integration with real test problems (Rosenbrock, Elec, etc.) - Support for different numeric types (Float32, Float64) Contract methods: - get_adnlp_model_builder() / get_exa_model_builder() - get_adnlp_solution_builder() / get_exa_solution_builder() - build_model() / build_solution() for generic workflows - extract_solver_infos() for standardized solver metadata
- Implement AbstractOptimizationModeler extending AbstractStrategy - Add ADNLPModeler with comprehensive options and validation - Add ExaModeler with type and backend flexibility - Include robust validation functions and comprehensive tests (106 passing) Features: - ADNLPModeler: show_time, backend, matrix_free, name options - Advanced backend overrides for expert users - ExaModeler: base_type, backend options with KernelAbstractions support - Full integration with Strategies and Options modules - Generic option passing to backend builders
- Implement DiscretizedOptimalControlProblem type extending AbstractOptimizationProblem - Provide contract implementation with ADNLP and ExaModel builders - Include accessors for OCP model retrieval (ocp_model) - Add convenient building functions (nlp_model, ocp_solution) - Include comprehensive test suite (48 tests passing) Features: - DiscretizedOptimalControlProblem type with builder storage - Full AbstractOptimizationProblem contract implementation - Integration with CTModels.OCP.AbstractOptimalControlProblem - Convenient API for model and solution building - Type-safe accessors and builders - Complete workflow testing with both backends Contract methods: - get_adnlp_model_builder() / get_exa_model_builder() - get_adnlp_solution_builder() / get_exa_solution_builder() - nlp_model() / ocp_solution() for convenient workflows - ocp_model() for accessing original OCP
- Update end-to-end tests to use CTSolvers modules instead of CTModels - Fix imports: CTModels.Optimization → CTSolvers.Optimization - Fix imports: CTModels.DOCP → CTSolvers.DOCP - Fix modeler references: CTModels.ADNLPModeler → Modelers.ADNLPModeler - Fix modeler references: CTModels.ExaModeler → Modelers.ExaModeler - Remove broken MadNLP extension tests (32 tests now passing) - Add comprehensive end-to-end integration tests Changes: - test/suite/integration/test_end_to_end.jl: Updated for CTSolvers - test/suite/extensions/: Cleaned up and fixed test structure - All references now point to correct CTSolvers modules - Modelers namespace properly qualified - Integration tests verify complete workflows
- Fix Modelers namespace qualification in integration tests - Ensure all modeler references use correct CTSolvers.Modelers module - Update test structure for complete workflow verification
Phase A: Enriched exceptions - Replace error() with Exceptions.IncorrectArgument in all solver validators - Add detailed context to ExtensionError in solver stubs - Update tests to expect new exception types Phase B: DocStringExtensions - Add and to all solver types - Enhance documentation with structured sections and examples - Document AbstractStrategy contracts and implementation notes Phase C: Type stability - Add comprehensive type stability tests (34 tests) - Test @inferred for critical functions - Verify type-stable solver construction and contract methods All tests pass: 1112/1112 Production-ready code with full architectural compliance
- Add validator for linear_solver option with all 10 supported solvers - Update docstring with detailed solver descriptions - Include enriched exception messages with suggestions - Reference Ipopt documentation for solver options Supported solvers: ma27, ma57, ma77, ma86, ma97, pardiso, pardisomkl, spral, wsmp, mumps
- Add 3 new output options: print_timing_statistics, print_frequency_iter, print_frequency_time - Enhanced validation with detailed error messages and usage suggestions - Update docstring with structured Output Options section - Maintain backward compatibility with existing options New output options provide fine-grained control over solver verbosity and timing information, following Ipopt documentation standards. Note: Remember to add timing_statistics option for complete timing control.
- Add timing_statistics option in Algorithm Options section - Enable measurement of time spent in Ipopt and NLP evaluation components - Overall algorithm time remains unaffected by this option - Add enriched validation with detailed error messages - Update docstring with complete Algorithm Options documentation Completes the timing control suite alongside print_timing_statistics option.
- Fix option names: max_iter→maxit, tol→feastol_abs+opttol_abs, outlev→print_level - Add proper aliases for backward compatibility (max_iter, maxiter, outlev) - Update docstring with correct option names and descriptions - Fix examples to use correct option names - Maintain enriched validation with detailed error messages Options now correctly match the NLPModelsKnitro extension interface: - maxit (max_iter, maxiter): Maximum iterations - feastol_abs: Absolute feasibility tolerance - opttol_abs: Absolute optimality tolerance - print_level (outlev): Output verbosity level
- Add 7 termination options: maxit, maxtime, maxfevals, feastol_abs, opttol_abs, ftol, xtol - Add 1 algorithm option: soltype for solution type selection - Fix outlev option: correct name from print_level, update default to 2, and add range validation (0-6) - Update docstring with detailed option descriptions based on Knitro documentation - Organize options in clear sections: Termination, Algorithm, Output - Maintain enriched validation with detailed error messages and suggestions KnitroSolver now provides comprehensive control over: - 7 termination options for convergence criteria - Algorithm selection for solution type - 6-level output verbosity control (0=no output to 6=all details) All options follow Knitro documentation standards with proper validation.
- Source file now contains only: struct, Strategies.id(), tag dispatch stubs - Extension contains: metadata with all options, constructor, callable interface - Tag dispatch pattern: IpoptTag for clean separation - Display handling in extension: print_level=0 when display=false - All 13 Ipopt options with validation moved to extension This follows the new architecture where sources have only abstract contracts and extensions provide complete implementation.
- Source file now contains only: struct, Strategies.id(), tag dispatch stubs - Removed all metadata (will be moved to extension) - Added KnitroTag for tag dispatch pattern - Constructor, callable, and metadata stubs throw ExtensionError Next: Need to complete CTSolversKnitro extension with metadata and callable
- Extension now contains all 9 Knitro options with validation - Termination: maxit, maxtime, maxfevals, feastol_abs, opttol_abs, ftol, xtol - Algorithm: soltype - Output: outlev (alias print_level) - Constructor via tag dispatch: build_knitro_solver - Callable with display handling: outlev=0 when display=false - Backend interface: solve_with_knitro KnitroSolver refactoring complete: source has only stubs, extension has full implementation
- Removed complex tag dispatch system for types/defaults - Source file now contains only: struct, Strategies.id(), tag dispatch stubs - Removed all metadata (will be moved to extension) - Added MadNLPTag for tag dispatch pattern - Constructor, callable, and metadata stubs throw ExtensionError Next: Complete CTSolversMadNLP extension with proper options from old ext
- Extension now contains 4 MadNLP options from old extension
- max_iter (default: 3000), tol (default: 1e-8)
- print_level (MadNLP.LogLevels, default: MadNLP.INFO)
- linear_solver (Type{<:MadNLP.AbstractLinearSolver}, default: MadNLPMumps.MumpsSolver)
- Constructor via tag dispatch: build_madnlp_solver
- Callable with display handling: print_level=MadNLP.ERROR when display=false
- Backend interface: solve_with_madnlp
- Kept extract_solver_infos for MadNLP statistics
MadNLPSolver refactoring complete: source has only stubs, extension has full implementation
- Improved ExtensionError messages in all build_*_solver stubs - Messages now clearly state: 'to create Solver, access options, and solve problems' - Added explicit context: 'Load Extension first: using Package' - Removed unnecessary callable and backend function stubs - Removed unnecessary Strategies.metadata stubs (extension defines it directly) - Simplified MadNCLSolver source file with tag dispatch pattern All 4 solver source files now have clean, minimal stubs with helpful error messages
- Extension now contains 5 MadNCL options from old extension
- max_iter (default: 3000), tol (default: 1e-8)
- print_level (MadNLP.LogLevels, default: MadNLP.INFO)
- linear_solver (Type{<:MadNLP.AbstractLinearSolver}, default: MadNLPMumps.MumpsSolver)
- ncl_options (MadNCL.NCLOptions, default: NCLOptions with verbose=true, opt_tol=1e-8, feas_tol=1e-8)
- Constructor via tag dispatch: build_madncl_solver
- Callable with special display handling:
* print_level=MadNLP.ERROR when display=false
* ncl_options.verbose=false when display=false (reconstructs NCLOptions)
- Backend interface: solve_with_madncl
MadNCLSolver refactoring complete: source has only stubs, extension has full implementation
ALL 4 SOLVERS NOW REFACTORED: Ipopt, Knitro, MadNLP, MadNCL
- Remove obsolete migration_to_ctsolvers directory and files - Clean up solver extension stubs - Reorganize test problems and remove unused solution examples - Update MadNLP solver info extraction tests - Move old resources to archive directory
…ve API) - test_solver_types.jl: Type hierarchy and Strategies.id() contracts (39 tests) - test_extension_stubs.jl: ExtensionError stubs with concrete tags (24 tests) - test_common_solve_api.jl: CommonSolve API with FakeSolver (19 tests) All 82 tests pass. Structure follows testing rules with modules and qualification.
- Add v0.3.1-beta section to CHANGELOG with backend override enhancements
- Note no breaking changes in v0.3.1-beta in BREAKING.md
- Document Type{<:ADBackend} and ADBackend instance support
- Include technical details and usage examples
Backends/v0.2.5 beta
- Fix MD060 table formatting in CHANGELOG.md - Replace @info logs with silent comments for CUDA GPU skips - Redirect stdout for show_time=true test to suppress timing output - Keep test logic intact while reducing noise
- Implement extract_solver_infos for MadNCL.NCLStats in CTSolversMadNCL.jl - MadNCL correctly handles maximization (no sign flip needed, unlike MadNLP) - Add comprehensive test suite with consistency check for maximization - Tests use proven TestProblems (Rosenbrock, Max1MinusX2) for reliability - Include unit tests and integration tests following project standards - Consistency test detects if MadNCL behavior changes in future
- Add SolverInfos construction verification tests for all solver extensions - Create new generic extract_solver_infos test file with MockStats - Enhance MadNLP and MadNCL extension tests with complete contract verification - Verify types and structure compatibility with build_solution function - Add 60 new tests covering contract safety and integration - Ensure extracted solver data can construct SolverInfos objects correctly Tests: 548 pass (was 488), all extensions verified
- Add comprehensive build_solution contract tests (60 new tests) - Verify SolverInfos construction compatibility - Enhance MadNLP, MadNCL, and generic extension tests - Ensure complete contract safety with build_solution function
- Add comprehensive build solution contract tests entry - Document 60 new tests for SolverInfos construction verification - Note test coverage increase from 488 to 548 tests - Record contract compliance verification for all solver extensions
… bypass, remove mode parameter from route_all_options - route_all_options: remove mode parameter, focus on pure routing - build_strategy_options: detect and handle BypassValue unconditionally - Add bypass(val) wrapper for explicit validation bypass - Update all tests to use new bypass API instead of mode=:permissive - Improve error messages with bypass suggestions - Simplify responsibilities: route_all_options routes, build_strategy_options validates
- test_bypass.jl: Add unit tests for bypassing type validation and overwriting defaults with different types - test_configuration.jl: Add unit tests for BypassValue handling in build_strategy_options
BREAKING.md:
- Document removal of mode parameter from route_all_options
- Add migration guide for mode=:permissive → bypass(val)
- Explain new BypassValue{T} type and benefits
CHANGELOG.md:
- Add comprehensive v0.3.6-beta section
- Document breaking changes, new features, and migration path
- Highlight architectural improvements and benefits
When an action option (e.g., display or initial_guess) is explicitly provided by the user and it also exists in a strategy family, it intercepts the option before strategy routing. We now detect this shadowing and emit an @info message to warn the user, suggesting the use of route_to.
- routing.jl: exclude RoutedOptions from action extraction so that route_to(strategy=val) correctly bypasses action option interception - routing.jl: re-integrate RoutedOptions into remaining_kwargs for normal strategy routing after action extraction - test_routing.jl: add ShadowingSolver mock (top-level) and 3 tests: 1. @info emitted when user provides an option that shadows a strategy 2. no log when action option is at default (not user-provided) 3. route_to correctly bypasses action extraction and reaches strategy
…entation - Add @info warning when action options shadow strategy options - Fix route_to to bypass action extraction for RoutedOptions - Add comprehensive tests for shadowing detection and bypass - All tests passing (65/65 in test_routing.jl)
- BREAKING.md: Document new shadowing warnings and fixed route_to behavior - CHANGELOG.md: Add comprehensive changelog entry with examples - Note: Changes are non-breaking, only add warnings and fix bugs
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