Methods for computing concepts, constellations, and integrated information of subsystems.

pyphi.compute.
concept
(subsystem, mechanism)¶ Return the concept specified by a mechanism within a subsytem.
Parameters:  subsystem (Subsytem) – The context in which the mechanism should be considered.
 mechanism (tuple(Node) – The candidate set of nodes.
Returns: concept –
 The pair of maximally irreducible cause/effect
repertoires that constitute the concept specified by the given mechanism.
Return type: Note
The output can be persistently cached to avoid recomputation. This may be enabled in the configuration file—however, it is only available if the caching backend is a database (not the filesystem). See the documentation for the
concept_caching
andconfig
modules.

pyphi.compute.
sequential_constellation
(subsystem, mechanism_indices_to_check=None)¶ Return the conceptual structure of this subsystem.
Parameters: subsystem (Subsystem) – The subsystem for which to determine the constellation. Returns: constellation –  A tuple of all the Concepts in the
 constellation.
Return type: ``tuple(Concept

pyphi.compute.
parallel_constellation
(subsystem, mechanism_indices_to_check=None)¶ Return the conceptual structure of this subsystem. Concepts are evaluated in parallel.
Parameters: subsystem (Subsystem) – The subsystem for which to determine the constellation. Returns: constellation –  A tuple of all the Concepts in the
 constellation.
Return type: ``tuple(Concept

pyphi.compute.
constellation
(subsystem, mechanism_indices_to_check=None)¶ Return the conceptual structure of this subsystem.
Parameters: subsystem (Subsystem) – The subsystem for which to determine the constellation. Returns: constellation –  A tuple of all the Concepts in the
 constellation.
Return type: ``tuple(Concept

pyphi.compute.
concept_distance
(c1, c2)¶ Return the distance between two concepts in conceptspace.
Parameters: Returns: distance –
 The distance between the two concepts in
conceptspace.
Return type: float

pyphi.compute.
constellation_distance
(C1, C2, subsystem)¶ Return the distance between two constellations in conceptspace.
Parameters:  C1 (tuple(Concept) – The first constellation.
 C2 (tuple(Concept) – The second constellation.
 null_concept (Concept) – The null concept of a candidate set, i.e the “origin” of the concept space in which the given constellations reside.
Returns: distance –
 The distance between the two constellations in
conceptspace.
Return type: float

pyphi.compute.
conceptual_information
(subsystem)¶ Return the conceptual information for a subsystem.
This is the distance from the subsystem’s constellation to the null concept.

pyphi.compute.
big_mip
(cache_key, subsystem)¶ Return the minimal information partition of a subsystem.
Parameters: subsystem (Subsystem) – The candidate set of nodes. Returns: big_mip –  A nested structure containing all the data from the
 intermediate calculations. The top level contains the basic MIP information for the given subsystem.
Return type: BigMip

pyphi.compute.
big_phi
(subsystem)¶ Return the \(\Phi\) value of a subsystem.

pyphi.compute.
subsystems
(network)¶ Return a generator of all possible subsystems of a network.

pyphi.compute.
all_complexes
(network)¶ Return a generator for all complexes of the network, including reducible, zerophi complexes (which are not, strictly speaking, complexes at all).

pyphi.compute.
possible_complexes
(network)¶ Return a generator of the subsystems of a network that could be a complex.
This is the just powerset of the nodes that have at least one input and output (nodes with no inputs or no outputs cannot be part of a main complex, because they do not have a causal link with the rest of the subsystem in the past or future, respectively).

pyphi.compute.
complexes
(network)¶ Return a generator for all irreducible complexes of the network.

pyphi.compute.
main_complex
(network)¶ Return the main complex of the network.

pyphi.compute.
condensed
(network)¶ Return the set of maximal nonoverlapping complexes.