pyhgf.updates.prediction.volatile.predict_precision_value_level_mean_field#

pyhgf.updates.prediction.volatile.predict_precision_value_level_mean_field(attributes, edges, node_idx)[source]#

Predict the precision of the value level using the implicit volatility level.

The volatility level’s mean modulates the value level’s precision.

Parameters:
  • attributes (dict) – The attributes of the probabilistic nodes.

  • edges (tuple[AdjacencyLists, ...]) – The edges of the probabilistic nodes as a tuple of pyhgf.typing.AdjacencyLists. For each node, the entry lists its value/volatility parents and children.

  • node_idx (int) – Pointer to the volatile-state node that will be updated.

Returns:

  • expected_precision – The expected (marginal) precision of the value level.

  • conditional_expected_precision – The conditional predicted precision of the value level.

  • effective_precision – The effective precision of the value-level prediction.

Return type:

tuple[Array, Array, Array]