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pygad-3.4.0.tar.gz 2025-01-07 105.8 kB
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README.md 2025-01-07 3.1 kB
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  1. The delay_after_gen parameter is removed from the pygad.GA class constructor. As a result, it is no longer an attribute of the pygad.GA class instances. To add a delay after each generation, apply it inside the on_generation callback. https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/283
  2. In the single_point_crossover() method of the pygad.utils.crossover.Crossover class, all the random crossover points are returned before the for loop. This is by calling the numpy.random.randint() function only once before the loop to generate all the K points (where K is the offspring size). This is compared to calling the numpy.random.randint() function inside the for loop K times, once for each individual offspring.
  3. Bug fix in the examples/example_custom_operators.py script. https://github.com/ahmedfgad/GeneticAlgorithmPython/pull/285
  4. While making prediction using the pygad.torchga.predict() function, no gradients are calculated.
  5. The gene_type parameter of the pygad.helper.unique.Unique.unique_int_gene_from_range() method accepts the type of the current gene only instead of the full gene_type list.
  6. Created a new method called unique_float_gene_from_range() inside the pygad.helper.unique.Unique class to find a unique floating-point number from a range.
  7. Fix a bug in the pygad.helper.unique.Unique.unique_gene_by_space() method to return the numeric value only instead of a NumPy array.
  8. Refactoring the pygad/helper/unique.py script to remove duplicate codes and reformatting the docstrings.
  9. The plot_pareto_front_curve() method added to the pygad.visualize.plot.Plot class to visualize the Pareto front for multi-objective problems. It only supports 2 objectives. https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/279
  10. Fix a bug converting a nested NumPy array to a nested list. https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/300
  11. The Matplotlib library is only imported when a method inside the pygad/visualize/plot.py script is used. This is more efficient than using import matplotlib.pyplot at the module level as this causes it to be imported when pygad is imported even when it is not needed. https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/292
  12. Fix a bug when minus sign (-) is used inside the stop_criteria parameter (e.g. stop_criteria=["saturate_10", "reach_-0.5"]). https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/296
  13. Make sure self.best_solutions is a list of lists inside the cal_pop_fitness method. https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/293
  14. Fix a bug where the cal_pop_fitness() method was using the previous_generation_fitness attribute to return the parents fitness. This instance attribute was not using the fitness of the latest population, instead the fitness of the population before the last one. The issue is solved by updating the previous_generation_fitness attribute to the latest population fitness before the GA completes. https://github.com/ahmedfgad/GeneticAlgorithmPython/issues/291
Source: README.md, updated 2025-01-07