pyphi.actual

Methods for computing actual causation of systems and mechanisms.

If you use this module, please cite the following papers:

Albantakis L, Marshall W, Hoel E, Tononi G (2019). What Caused What? A quantitative Account of Actual Causation Using Dynamical Causal Substrates. Entropy, 21 (5), pp. 459. https://doi.org/10.3390/e21050459

Mayner WGP, Marshall W, Albantakis L, Findlay G, Marchman R, Tononi G. (2018). PyPhi: A toolbox for integrated information theory. PLOS Computational Biology 14(7): e1006343. https://doi.org/10.1371/journal.pcbi.1006343

Functions

account(transition[, direction])	Return the set of all causal links for a Transition.
causal_nexus(substrate, before_state, ...[, ...])	Return the causal nexus of the substrate.
directed_account(transition, direction[, ...])	Return every causal link of the specified direction.
events(substrate, previous_state, ...[, ...])	Find all events (mechanisms with actual causes and actual effects).
extrinsic_events(substrate, previous_state, ...)	Set of all mechanisms that are in the major complex but which have true causes and effects within the entire substrate.
nexus(substrate, before_state, after_state)	Return a tuple of all irreducible nexus of the substrate.
nice_true_ces(tc)	Format a true Distinctions.
sia(transition[, direction])	Return the minimal information partition of a transition in a specific direction.
transitions(substrate, before_state, after_state)	Return a generator over all realizable transitions of a substrate.
true_ces(system, previous_state, next_state)	Set of all sets of elements that have true causes and true effects.
true_events(substrate, previous_state, ...)	Return all mechanisms that have true causes and true effects within the complex.

Classes

Transition(substrate, before_state, ...[, ...])	A state transition over a substrate, holding two TransitionSystem views.
TransitionSystem(substrate, before_state, ...)	A directional view of a state transition.