categorical#

class brainpy.math.random.categorical(logits, axis=-1, size=None, key=None)[source]#

Sample random values from categorical distributions.

Parameters:

  • logits – Unnormalized log probabilities of the categorical distribution(s) to sample from, so that softmax(logits, axis) gives the corresponding probabilities.

  • axis (int) – Axis along which logits belong to the same categorical distribution.

  • shape – Optional, a tuple of nonnegative integers representing the result shape. Must be broadcast-compatible with np.delete(logits.shape, axis). The default (None) produces a result shape equal to np.delete(logits.shape, axis).

  • key – a PRNG key used as the random key.

Returns:

A random array with int dtype and shape given by shape if shape is not None, or else np.delete(logits.shape, axis).