slim_gsgp.algorithms.SLIM_GSGP.representations

slim_gsgp.algorithms.SLIM_GSGP.representations.individual

slim_gsgp.algorithms.SLIM_GSGP.representations.population

Population Class for SLIM GSGP using PyTorch.

class slim_gsgp.algorithms.SLIM_GSGP.representations.population.Population(population)[source]

Bases: object

calculate_semantics(inputs, testing=False)[source]

Calculate the semantics for each individual in the population.

Parameters:

  • inputs (torch.Tensor) – Input data for calculating semantics.

  • testing (bool, optional) – Boolean indicating if the calculation is for testing semantics.

Return type:

None

evaluate(ffunction, y, operator='sum', n_jobs=1)[source]

Evaluate the population using a fitness function.

Parameters:

  • ffunction (Callable) – Fitness function to evaluate the individuals.

  • y (torch.Tensor) – Expected output (target) values.

  • operator (str, optional) – Operator to apply to the semantics (“sum” or “prod”). Default is “sum”.

  • n_jobs (int, optional) – The maximum number of concurrently running jobs for joblib parallelization. Default is 1.

Return type:

None

evaluate_no_parall(ffunction, y, operator='sum')[source]

Evaluate the population using a fitness function (without parallelization). This function is not currently in use, but has been retained for potential future use at the developer’s discretion.

Parameters:

  • ffunction (Callable) – Fitness function to evaluate the individuals.

  • y (torch.Tensor) – Expected output (target) values.

  • operator (str, optional) – Operator to apply to the semantics. Default is “sum”.

Return type:

None