populate

PopulateDefault

populate(self, *, pospool, posmap, population_size, probcol='prob', **kwargs)

Creates individuals in population

Parameters:

Name	Type	Description	Default
pospool	Dict[str, DataFrame]	pool split into positions	required
posmap	Dict[str, int]	positions & accompanying roster slots	required
population_size	int	number of individuals to create	required
probcol	str	the dataframe column with probabilities	'prob'
**kwargs		keyword arguments	{}

Returns:

Type	Description
ndarray	ndarray of size (population_size, sum(posmap.values()))

Source code in pangadfs/populate.py

def populate(self,
             *, 
             pospool, 
             posmap: Dict[str, int], 
             population_size: int, 
             probcol: str='prob',
             **kwargs) -> np.ndarray:
    """Creates individuals in population

    Args:
        pospool (Dict[str, DataFrame]): pool split into positions
        posmap (Dict[str, int]): positions & accompanying roster slots
        population_size (int): number of individuals to create
        probcol (str): the dataframe column with probabilities
        **kwargs: keyword arguments

    Returns:
        ndarray of size (population_size, sum(posmap.values()))

    """
    pos_samples = {
        pos: multidimensional_shifting(pospool[pos].index, population_size, n, pospool[pos][probcol])
        for pos, n in posmap.items()
    }

    # concatenate positions into single row
    pop = np.concatenate([pos_samples[pos] for pos in posmap if pos != 'FLEX'], axis=1)

    # find non-duplicate FLEX and aggregate with other positions
    # https://stackoverflow.com/questions/65473095
    # https://stackoverflow.com/questions/54155844/
    dups = (pos_samples['FLEX'][..., None] == pop[:, None, :]).any(-1)
    return np.column_stack((pop, pos_samples['FLEX'][np.invert(dups).cumsum(axis=1).cumsum(axis=1) == 1]))