frlearn.array_functions.soft_max

frlearn.array_functions.soft_max(a, weights, k: int, axis=-1, type: str = 'arithmetic')

Calculates the soft maximum of an array.

Parameters:

andarray

Input array of values.

weights(k -> np.array) or None

Weights to apply to the k selected values. If None, the kth value is returned.

k: int or None

Number of greatest values from which the soft maximum is calculated. Should be either a positive integer not larger than a along axis, or None, which is interpreted as the size of a along axis.

axisint, default=-1

The axis along which the soft maximum is calculated.

typestr {‘arithmetic’, ‘geometric’, ‘harmonic’, }, default=’arithmetic’

Determines the type of weighted average.

Returns:

soft_max_along_axisndarray

An array with the same shape as a, with the specified axis removed. If a is a 0-d array, a scalar is returned.