validate

DuplicatesValidate

validate(self, *, population, **kwargs)

Removes duplicate individuals from population

Parameters:

Name	Type	Description	Default
population	ndarray	the population to validate	required
**kwargs		keyword arguments for plugins	{}

Returns:

Type	Description
ndarray	np.ndarray: same width as population, likely has less rows

Source code in pangadfs/validate.py

def validate(self,
             *, 
             population: np.ndarray, 
             **kwargs) -> np.ndarray:
    """Removes duplicate individuals from population

        Args:
            population (np.ndarray): the population to validate
            **kwargs: keyword arguments for plugins

        Returns:
            np.ndarray: same width as population, likely has less rows

    """
    # the first part eliminates individuals with duplicate genes
    # the second part eliminates duplicate individuals
    population_sorted = np.sort(population, axis=-1)
    population = population[(population_sorted[...,1:] != population_sorted[..., :-1]).all(-1)]
    return unique(np.sort(population, axis=1))

SalaryValidate

validate(self, *, population, salaries, salary_cap, **kwargs)

Ensures valid individuals in population

Parameters:

Name	Type	Description	Default
population	ndarray	the population to validate	required
salaries	ndarray	1D where indices are in same order as player indices	required
salary_cap	int	the salary cap, e.g., 50000 or 60000	required
**kwargs		keyword arguments for plugins	{}

Returns:

Type	Description
ndarray	np.ndarray: same width as population, likely has less rows

Source code in pangadfs/validate.py

def validate(self,
             *, 
             population: np.ndarray,
             salaries: np.ndarray,
             salary_cap: int, 
             **kwargs) -> np.ndarray:
    """Ensures valid individuals in population

        Args:
            population (np.ndarray): the population to validate
            salaries (np.ndarray): 1D where indices are in same order as player indices
            salary_cap (int): the salary cap, e.g., 50000 or 60000
            **kwargs: keyword arguments for plugins

        Returns:
            np.ndarray: same width as population, likely has less rows

    """
    popsal = np.sum(salaries[population], axis=1)
    return population[popsal <= salary_cap]