network
¶
Represents the network of interest. This is the primary object of PyPhi and the context of all \(\varphi\) and \(\Phi\) computation.
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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. Returns: network – The corresponding PyPhi network object. Return type: Network
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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: tpm (np.ndarray) – See the corresponding attribute. Keyword Arguments: 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 thattpm[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 thattpm[(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]
, whereS
is the number of states andN
is the number of nodes in the network.
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connectivity_matrix
¶ np.ndarray – A square binary adjacency matrix indicating the connections between nodes in the network.
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size
¶ int – The number of nodes in the network.
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num_states
¶ int – The number of possible states of the network.
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size
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num_states
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node_indices
¶
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tpm
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connectivity_matrix
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perturb_vector
¶
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__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.
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to_json
()¶
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