node
¶
Represents a node in a subsystem. Each node has a unique index, its position in the network’s list of nodes.

class
pyphi.node.
Node
(network, index, subsystem, label=None)¶ A node in a subsystem.

network
¶ network – The network the node belongs to.

index
¶ int – The node’s index in the network’s list of nodes.

subsystem
¶ Subsystem – The subsystem the node belongs to.

label
¶ str – An optional label for the node.

inputs
¶ list(Node – A list of nodes that have connections to this node.

past_tpm
¶ np.ndarray – The TPM for this node, conditioned on the past state of the boundary nodes, whose states are fixed.
this_node.past_tpm[0]
andthis_node.past_tpm[1]
gives the probability tables that this node is off and on, respectively, indexed by subsystem state, after marginalizingout nodes that don’t connect to this node.

current_tpm
¶ np.ndarray – Same as
past_tpm
, but conditioned on the current state of the boundary nodes.
Examples
In a 3node subsystem,
self.past_tpm[0][(0, 0, 1)]
gives the probability that this node is off at \(t_0\) if the state of the network is \(\{N_0 = 0, N_1 = 0, N_2 = 1\}\) at \(t_{1}\).Similarly,
self.current_tpm[1][(0, 0, 1)]
gives the probability that this node is on at t_1 if the state of the network is \(\{N_0 = 0, N_1 = 0, N_2 = 1\}\) at \(t_0\).
get_marbl
(direction, normalize=True)¶ Generate a Marbl for this node, using either the past or current TPM.

inputs
The set of nodes with connections to this node.

outputs
¶ The set of nodes this node has connections to.

past_marbl
¶ The normalized representation of this node’s Markov blanket, conditioned on the fixed state of boundarycondition nodes in the previous timestep.

current_marbl
¶ The normalized representation of this node’s Markov blanket, conditioned on the fixed state of boundarycondition nodes in the current timestep.

raw_past_marbl
¶ The unnormalized representation of this node’s Markov blanket, conditioned on the fixed state of boundarycondition nodes in the previous timestep.

raw_current_marbl
¶ The unnormalized representation of this node’s Markov blanket, conditioned on the fixed state of boundarycondition nodes in the current timestep.

__eq__
(other)¶ Return whether this node equals the other object.
Two nodes are equal if they belong to the same subsystem and have the same index (their TPMs must be the same in that case, so this method doesn’t need to check TPM equality).
Labels are for display only, so two equal nodes may have different labels.

json_dict
()¶
