# network¶

Represents the network of interest. This is the primary object of PyPhi and the context of all $$\varphi$$ and $$\Phi$$ computation.

pyphi.network.from_json(filename)

Convert a JSON representation of a network to a PyPhi network.

Parameters: filename (str) – A path to a JSON file representing a network. network – The corresponding PyPhi network object. Network
class pyphi.network.Network(tpm, connectivity_matrix=None, perturb_vector=None, purview_cache=None)

A network of nodes.

Represents the network we’re analyzing and holds auxilary data about it.

Example

In a 3-node network, a_network.tpm[(0, 0, 1)] gives the transition probabilities for each node at $$t_0$$ given that state at $$t_{-1}$$ was $$\{N_0 = 0, N_1 = 0, N_2 = 1\}$$.

Parameters: Keyword Arguments: tpm (np.ndarray) – See the corresponding attribute. connectivity_matrix (array or sequence) – A square binary adjacency matrix indicating the connections between nodes in the network. connectivity_matrix[i][j] == 1 means that node $$i$$ is connected to node $$j$$. If no connectivity matrix is given, every node is connected to every node (including itself).
tpm

np.ndarray – The network’s transition probability matrix. It can be provided in either state-by-node (either 2-D or N-D) or state-by-state form. In either form, row indices must follow the LOLI convention (see discussion in the examples module), and in state-by-state form, so must column indices. If given in state-by-node form, it can be either 2-dimensional, so that tpm[i] gives the probabilities of each node being on if the past state is encoded by $$i$$ according to LOLI, or in N-D form, so that tpm[(0, 0, 1)] gives the probabilities of each node being on if the past state is $$\{N_0 = 0, N_1 = 0, N_2 = 1\}$$. The shape of the 2-dimensional form of a state-by-node TPM must be (S, N), and the shape of the N-D form of the TPM must be [2] * N + [N], where S is the number of states and N is the number of nodes in the network.

connectivity_matrix

np.ndarray – A square binary adjacency matrix indicating the connections between nodes in the network.

size

int – The number of nodes in the network.

num_states

int – The number of possible states of the network.

size
num_states
node_indices
tpm
connectivity_matrix
perturb_vector
__eq__(other)

Return whether this network equals the other object.

Two networks are equal if they have the same TPM, connectivity matrix, and perturbation vector.

to_json()