`models.actual_causation`¶

Objects that represent structures used in actual causation.

pyphi.models.actual_causation.greater_than_zero(alpha)¶: Return True if alpha is greater than zero, accounting for numerical errors.

class pyphi.models.actual_causation.AcRepertoireIrreducibilityAnalysis(alpha, state, direction, mechanism, purview, partition, probability, partitioned_probability, node_labels=None)¶

A minimum information partition for ac_coef calculation.

These can be compared with the built-in Python comparison operators (<, >, etc.). First, \(\alpha\) values are compared. Then, if these are equal up to PRECISION, the size of the mechanism is compared.

alpha¶

This is the difference between the mechanism’s unpartitioned and partitioned actual probability.

Type: float

state¶

state of system in specified direction (cause, effect)

Type: tuple[int]

direction¶

The temporal direction specifiying whether this analysis should be calculated with cause or effect repertoires.

Type: str

mechanism¶

The mechanism to analyze.

Type: tuple[int]

purview¶

The purview over which the unpartitioned actual probability differs the least from the actual probability of the partition.

Type: tuple[int]

partition¶

The partition that makes the least difference to the mechanism’s repertoire.

Type: tuple[Part, Part]

probability¶

The probability of the state in the previous/next timestep.

Type: float

partitioned_probability¶

The probability of the state in the partitioned repertoire.

Type: float

unorderable_unless_eq = ['direction']¶

order_by()¶

Return a list of values to compare for ordering.

The first value in the list has the greatest priority; if the first objects are equal the second object is compared, etc.

__bool__()¶: An AcRepertoireIrreducibilityAnalysis is True if it has \(\alpha > 0\).

property phi¶: Alias for \(\alpha\) for PyPhi utility functions.

to_json()¶: Return a JSON-serializable representation.

class pyphi.models.actual_causation.CausalLink(ria)¶

A maximally irreducible actual cause or effect.

These can be compared with the built-in Python comparison operators (<, >, etc.). First, \(\alpha\) values are compared. Then, if these are equal up to PRECISION, the size of the mechanism is compared.

property alpha¶

The difference between the mechanism’s unpartitioned and partitioned actual probabilities.

Type: float

property phi¶: Alias for \(\alpha\) for PyPhi utility functions.

property direction¶

Either CAUSE or EFFECT.

Type: Direction

property mechanism¶

The mechanism for which the action is evaluated.

Type: list[int]

property purview¶

The purview over which this mechanism’s \(\alpha\) is maximal.

Type: list[int]

property ria¶

The irreducibility analysis for this mechanism.

Type: AcRepertoireIrreducibilityAnalysis

property node_labels¶

unorderable_unless_eq = ['direction']¶

order_by()¶

Return a list of values to compare for ordering.

The first value in the list has the greatest priority; if the first objects are equal the second object is compared, etc.

__bool__()¶: An CausalLink is True if \(\alpha > 0\).

to_json()¶: Return a JSON-serializable representation.

class pyphi.models.actual_causation.Event(actual_cause, actual_effect)¶

A mechanism which has both an actual cause and an actual effect.

actual_cause¶

The actual cause of the mechanism.

Type: CausalLink

actual_effect¶

The actual effect of the mechanism.

Type: CausalLink

Create new instance of Event(actual_cause, actual_effect)

property mechanism¶: The mechanism of the event.

class pyphi.models.actual_causation.Account(causal_links)¶

The set of CausalLink with \(\alpha > 0\). This includes both actual causes and actual effects.

property irreducible_causes¶: The set of irreducible causes in this Account.

property irreducible_effects¶: The set of irreducible effects in this Account.

to_json()¶

classmethod from_json(dct)¶

class pyphi.models.actual_causation.DirectedAccount(causal_links)¶: The set of CausalLink with \(\alpha > 0\) for one direction of a transition.

class pyphi.models.actual_causation.AcSystemIrreducibilityAnalysis(alpha=None, direction=None, account=None, partitioned_account=None, transition=None, cut=None)¶

An analysis of transition-level irreducibility (\(\mathcal{A}\)).

Contains the \(\mathcal{A}\) value of the Transition, the causal account, and all the intermediate results obtained in the course of computing them.

alpha¶

The \(\mathcal{A}\) value for the transition when taken against this analysis, i.e. the difference between the unpartitioned account and this analysis’s partitioned account.

Type: float

account¶

The account of the whole transition.

Type: Account

partitioned_account¶

The account of the partitioned transition.

Type: Account

transition¶

The transition this analysis was calculated for.

Type: Transition

cut¶

The minimal partition.

Type: ActualCut

property before_state¶: Return the actual previous state of the Transition.

property after_state¶: Return the actual current state of the Transition.

unorderable_unless_eq = ['direction']¶

order_by()¶

Return a list of values to compare for ordering.

The first value in the list has the greatest priority; if the first objects are equal the second object is compared, etc.

__bool__()¶: An AcSystemIrreducibilityAnalysis is True if it has \(\mathcal{A} > 0\).

to_json()¶

models.actual_causation¶

`models.actual_causation`¶