Network

Control of model network definition and dynamics.

The network module includes efficient functions for running core mechanisms of CMR. These functions will generally not be called directly by users. See the cmr module for high-level functions for running parameter searches and simulations using CMR.

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.