Network

Network Initialization

Network(f_segment, c_segment)

Representation of interacting item and context layers.

Accessing and Setting Values

Network.copy([include, exclude])	Copy the network to a new network object.
Network.reset()	Reset network weights and activations to zero.
Network.get_sublayer(layer, sublayer)	Get indices for a sublayer.
Network.get_sublayers(layer, sublayers)	Get an array of indices for multiple sublayers.
Network.get_segment(layer, sublayer, segment)	Get indices for a segment.
Network.get_unit(layer, sublayer, segment, unit)	Get indices for a unit.
Network.add_pre_weights(connect, f_segment, ...)	Add pre-experimental weights to a network.

Operations

Network.update(item, sublayers)	Update context completely with input from the item layer.
Network.integrate(item, sublayers, B)	Integrate input from the item layer into context.
Network.present(item, sublayers, B[, Lfc, Lcf])	Present an item and learn context-item associations.
Network.learn(connect, item, sublayers, L)	Learn an association between the item and context layers.

Simulating Tasks

Network.study(segment, item_list, sublayers, ...)	Study a list of items.
Network.p_recall(segment, recalls, ...[, amin])	Calculate the probability of a specific recall sequence.
Network.generate_recall(segment, sublayers, ...)	Generate a sequence of simulated free recall events.
Network.generate_recall_lba(segment, ...)	Generate timed free recall using the LBA model.

Recording and Visualization

Network.record_study(segment, item_list, ...)	Study a list of items and record network states.
Network.record_recall(segment, recalls, ...)	Simulate a recall sequence and record network states.
Network.plot([ax])	Plot the current state of the network.