BioGA 0.99.17
Added: - Demo vignette for BioGA. - Mathematical background vignette for BioGA.
Updated: - BioGA vignettes with new examples and explanations. - selection_cpp function for improved performance and bug fixes.
BioGA 0.99.16
UPDATE: test_crossover_cpp
The test verifies dimensions, value ranges, and new parameters.
Changes: - Added tests for new parameters (crossover_rate, eta_c). - Verified that offspring values lie within parent ranges (due to SBX). - Included edge case test for single parent and zero crossover rate. - Simplified error/warning checks.
UPDATE: test_selection_cpp The test checks dimensions, parent selection, and compatibility with multi-objective fitness.
Changes: - Updated to handle multi-objective fitness matrix. - Verified that selected parents are exact copies of population rows. - Added edge case test for single individual and single objective. - Removed redundant fitness evaluation test (already covered in evaluate_fitness_cpp).
UPDATE: test_mutation_cpp The test checks dimensions, mutation effects, and new parameters.
Changes: - Added tests for new parameters (iteration, max_iterations, network). - Verified that zero mutation rate preserves offspring. - Tested network constraints with extreme cases (zero and full constraints). - Simplified error/warning checks.
UPDATE/ADDED: test_replacement_cpp
The test checks dimensions, elite preservation, and diversity.
Changes: - Added test for new function signature (requires fitness matrices). - Verified elite preservation based on first objective. - Included edge case test for zero replacements. - Added checks for dimensions and error-free execution.
UPDATE: test_initialize_population_cpp
The test checks dimensions, value validity, and new parameters.
Changes: - Added test for seed parameter to ensure reproducibility. - Included test for clusters parameter to verify correct initialization. - Maintained tests for dimensions and value validity. - Added edge case test for minimal input.
UPDATE: test_bioga_main_cpp {PROVISIONAL}
New test file is created to verify the main GA loop.
Feature: - Tests the output structure (list with population and fitness). - Verifies dimensions of population and fitness matrices. - Checks optional parameters (clusters, network). - Includes edge case test for minimal input.
Test for Package (test-BioGA-package.R)
Created a new version to test the overall package integrity and ensure all functions are exported correctly.
Feature: - Tests package loading and function exports. - Verifies a complete GA workflow without errors. - Ensures compatibility with the optimized functions.
BioGA 0.99.15
UPDATE: test_evaluate_fitness_cpp The test checks dimensions, values, and error-free execution.
Changes:
- Updated to test the new matrix output (multiple objectives).
- Added checks for non-negative fitness values (appropriate for expression difference and sparsity).
- Included edge case test for minimal input.
- Removed redundant
tryCatchand simplified error/warning checks.
BioGA 0.99.14
Commit -m “New Feature - Main GA Loop”
adding a main GA loop function that integrates all components and supports multi-objective optimization and parallelization.
Features:
- Integrates all optimized components into a cohesive GA loop.
- Supports multi-objective optimization, gene networks, and clustering.
- Returns both final population and fitness scores for analysis.
BioGA 0.99.13
Commit -m “Optimized initialize_population.cpp”
Improvements:
- Add option for biologically informed initialization using gene clusters.
- Improve random seed handling for reproducibility.
Changes:
- Added optional random seed for reproducibility.
- Included support for gene clustering to initialize biologically relevant populations.
- Improved code readability and documentation.
BioGA 0.99.11
Commit -m “Optimized replacement.cpp”
Improvements:
- Implement elitism to preserve best individuals.
- Add diversity-based replacement to avoid premature convergence.
Changes:
- Added elitism to preserve the best individual.
- Included diversity-based replacement to maintain population diversity.
- Updated to use multi-objective fitness matrix.
BioGA 0.99.10
Commit -m “Optimized mutation.cpp”
Improvements:
- Add adaptive mutation rate based on iteration or fitness stagnation.
- Incorporate gene network constraints (placeholder for user-provided network).
Changes:
- Added adaptive mutation rate based on iteration progress.
- Included optional gene network constraints to ensure biologically relevant mutations.
- Maintained compatibility with existing functionality.
BioGA 0.99.9
Commit -m “Optimized selection.cpp”
Improvements:
- Implement NSGA-II non-dominated sorting for multi-objective optimization.
- Add tournament selection for better diversity.
Changes:
- Implemented NSGA-II non-dominated sorting for multi-objective selection.
- Added tournament selection to maintain diversity.
- Updated to handle multi-objective fitness matrix.
BioGA 0.99.8
Commit -m “Optimized crossover.cpp” ” Improvements:
- Implement simulated binary crossover (SBX) for better exploration.
- Add adaptive crossover rate based on population diversity.
Changes:
- Replaced simple averaging with SBX crossover for better exploration.
- Added adaptive crossover rate based on population diversity.
- Included parameters for crossover rate and distribution index.
BioGA 0.99.7
Commit -m “Optimized evaluate_fitness.cpp”
Improvements:
- Add multi-objective fitness evaluation (e.g., minimize expression difference and maximize gene sparsity).
- Use vectorized operations for faster computation.
- Add parallelization with RcppParallel for large datasets.
Changes:
- Added multi-objective support (expression difference and sparsity).
- Used
RcppParallelfor parallel computation. - Returned a matrix of fitness scores for each objective.
- Added weights parameter for flexible objective prioritization.