PyGAD 3.0.1

Fix an issue with passing user-defined function/method for parent selection. ahmedfgad#179

PyGAD 3.0.0 Release

PyGAD 3.0.0 Release Notes
1. The structure of the library is changed and some methods defined in the `pygad.py` module are moved to the `pygad.utils`, `pygad.helper`, and `pygad.visualize` submodules.
  2. The `pygad.utils.parent_selection` module has a class named `ParentSelection` where all the parent selection operators exist. The `pygad.GA` class extends this class.
  3. The `pygad.utils.crossover` module has a class named `Crossover` where all the crossover operators exist. The `pygad.GA` class extends this class.
  4. The `pygad.utils.mutation` module has a class named `Mutation` where all the mutation operators exist. The `pygad.GA` class extends this class.
  5. The `pygad.helper.unique` module has a class named `Unique` some helper methods exist to solve duplicate genes and make sure every gene is unique. The `pygad.GA` class extends this class.
  6. The `pygad.visualize.plot` module has a class named `Plot` where all the methods that create plots exist. The `pygad.GA` class extends this class.

```python
...
class GA(utils.parent_selection.ParentSelection,
         utils.crossover.Crossover,
         utils.mutation.Mutation,
         helper.unique.Unique,
         visualize.plot.Plot):
...
```

2. Support of using the `logging` module to log the outputs to both the console and text file instead of using the `print()` function. This is by assigning the `logging.Logger` to the new `logger` parameter. Check the [Logging Outputs](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#logging-outputs) for more information.
3. A new instance attribute called `logger` to save the logger.
4. The function/method passed to the `fitness_func` parameter accepts a new parameter that refers to the instance of the `pygad.GA` class. Check this for an example: [Use Functions and Methods to Build Fitness Function and Callbacks](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#use-functions-and-methods-to-build-fitness-and-callbacks). ahmedfgad#163
5. Update the documentation to include an example of using functions and methods to calculate the fitness and build callbacks. Check this for more details: [Use Functions and Methods to Build Fitness Function and Callbacks](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#use-functions-and-methods-to-build-fitness-and-callbacks). ahmedfgad#92 (comment)
6. Validate the value passed to the `initial_population` parameter.
7. Validate the type and length of the `pop_fitness` parameter of the `best_solution()` method.
8. Some edits in the documentation. ahmedfgad#106
9. Fix an issue when building the initial population as (some) genes have their value taken from the mutation range (defined by the parameters `random_mutation_min_val` and `random_mutation_max_val`) instead of using the parameters `init_range_low` and `init_range_high`.
10. The `summary()` method returns the summary as a single-line string. Just log/print the returned string it to see it properly.
11. The `callback_generation` parameter is removed. Use the `on_generation` parameter instead.
12. There was an issue when using the `parallel_processing` parameter with Keras and PyTorch. As Keras/PyTorch are not thread-safe, the `predict()` method gives incorrect and weird results when more than 1 thread is used. ahmedfgad#145 ahmedfgad/TorchGA#5 ahmedfgad/KerasGA#6. Thanks to this [StackOverflow answer](https://stackoverflow.com/a/75606666/5426539).
13. Replace `numpy.float` by `float` in the 2 parent selection operators roulette wheel and stochastic universal. ahmedfgad#168

PyGAD 2.19.2 Release

PyGAD 2.19.2 Release Notes
1. Fix an issue when paralell processing was used where the elitism solutions' fitness values are not re-used. ahmedfgad#160 (comment)

PyGAD 2.19.1 Release

PyGAD 2.19.1 Release Notes
1. Add the [cloudpickle](https://github.com/cloudpipe/cloudpickle) library as a dependency.

Update conf.py

PyGAD 2.18.2

PyGAD 2.18.1 Documentation

PyGAD 2.18.0 Documentation

1. Raise an exception if the sum of fitness values is zero while either roulette wheel or stochastic universal parent selection is used. ahmedfgad#129
2. Initialize the value of the `run_completed` property to `False`. ahmedfgad#122
3. The values of these properties are no longer reset with each call to the `run()` method `self.best_solutions, self.best_solutions_fitness, self.solutions, self.solutions_fitness`: ahmedfgad#123. Now, the user can have the flexibility of calling the `run()` method more than once while extending the data collected after each generation. Another advantage happens when the instance is loaded and the `run()` method is called, as the old fitness value are shown on the graph alongside with the new fitness values. Read more in this section: [Continue without Loosing Progress](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#continue-without-loosing-progress)
4. Thanks [Prof. Fernando Jiménez Barrionuevo](http://webs.um.es/fernan) (Dept. of Information and Communications Engineering, University of Murcia, Murcia, Spain) for editing this [comment](https://github.com/ahmedfgad/GeneticAlgorithmPython/blob/5315bbec02777df96ce1ec665c94dece81c440f4/pygad.py#L73) in the code. ahmedfgad@5315bbe
5. A bug fixed when `crossover_type=None`.
6. Support of elitism selection through a new parameter named `keep_elitism`. It defaults to 1 which means for each generation keep only the best solution in the next generation. If assigned 0, then it has no effect. Read more in this section: [Elitism Selection](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#elitism-selection). ahmedfgad#74
7. A new instance attribute named `last_generation_elitism` added to hold the elitism in the last generation.
8. A new parameter called `random_seed` added to accept a seed for the random function generators. Credit to this issue ahmedfgad#70 and [Prof. Fernando Jiménez Barrionuevo](http://webs.um.es/fernan). Read more in this section: [Random Seed](https://pygad.readthedocs.io/en/latest/README_pygad_ReadTheDocs.html#random-seed).
9. Editing the `pygad.TorchGA` module to make sure the tensor data is moved from GPU to CPU. Thanks to Rasmus Johansson for opening this pull request: ahmedfgad/TorchGA#2

Change version to 2.17.0

PyGAD 2.16.3 Documentation