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ask for new features about fitness_func #163

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whubaichuan opened this issue Feb 24, 2023 · 7 comments
Closed

ask for new features about fitness_func #163

whubaichuan opened this issue Feb 24, 2023 · 7 comments
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enhancement New feature or request

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@whubaichuan
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Hi, for function fitness_func(solution,solution_idx):, can you add a new input variable such as fitness_func(solution,solution_idx, ga_instance): or fitness_func(solution,solution_idx, generations_completed):? Because I want to do some different calculate of fitness for different generations.
@ahmedfgad
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ahmedfgad commented Feb 24, 2023 •
edited

Can you use the on_fitness() callback to do your calculations? There the ga_instance is passed.

The fitness of the population will be passed to on_fitness().

@whubaichuan
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@ahmedfgad Hej, thanks for your quick reply. Actually, I want to change my fitness_func according to the ga_instance.generations_completed. For example, for the last generation, I want to change some hyperparameters in the fitness_func. Although this could be achieved by calculating the fitness of ga_instance.population manually after ga_instance.run() by adjusting a new fitness_function, how can I do it for example, the 2nd or 4th generation in general?

@whubaichuan
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whubaichuan commented Feb 25, 2023 •
edited

@ahmedfgad or could you slightly modify the capsulated Pygad-multiprocess function to make the change of generation_idx can be passed to the fitness_func()?

import signal
import time
import sys
import multiprocessing

generation_idx = 0

def change_idx():
    global generation_idx
    generation_idx =generation_idx+ 1
    print(generation_idx)

def fitness_func():
   
    print("generation_idx = {0}\n".format(generation_idx))
    time.sleep(1)

def main():
    for i in range(3):
        change_idx()
        worker = multiprocessing.Process(target=fitness_func, args=())
        worker.start()
        worker.join()


if __name__ == "__main__":
    main()


output:

1
generation_idx = 0

2
generation_idx = 0

3
generation_idx = 0

@ahmedfgad ahmedfgad added the enhancement New feature or request label Feb 25, 2023
@ahmedfgad
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@whubaichuan,

The ga_instance will be passed to the fitness function in the next release. Thank you!

@whubaichuan
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@ahmedfgad Thanks, looking forward to that.

ahmedfgad added a commit that referenced this issue Apr 8, 2023
@ahmedfgad
PyGAD 3.0.0 Release
6659d5d 
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). #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). #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. #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. #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. #168
@ahmedfgad
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@whubaichuan, PyGAD 3.0.0 is released and the GA instance is passed to the fitness function/method.

@whubaichuan
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@ahmedfgad Thanks a lot.

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@ahmedfgad @whubaichuan