# 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.AcMip

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

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

state

tuple[int] – state of system in specified direction (past, future)

direction

str – The temporal direction specifiying whether this AcMIP should be calculated with cause or effect repertoires.

mechanism

tuple[int] – The mechanism over which to evaluate the AcMIP.

purview

tuple[int] – The purview over which the unpartitioned actual probability differs the least from the actual probability of the partition.

partition

tuple[Part, Part] – The partition that makes the least difference to the mechanism’s repertoire.

probability

float – The probability of the state in the past/future.

partitioned_probability

float – The probability of the state in the partitioned repertoire.

Create new instance of AcMip(alpha, state, direction, mechanism, purview, partition, probability, partitioned_probability)

unorderable_unless_eq = ['direction']
order_by()
__bool__()

An AcMip is True if it has $$\alpha > 0$$.

phi

Alias for $$\alpha$$ for PyPhi utility functions.

to_json()

Return a JSON-serializable representation.

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.

alpha

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

phi

Alias for $$\alpha$$ for PyPhi utility functions.

direction

Direction – Either PAST or FUTURE.

mechanism

list[int] – The mechanism for which the action is evaluated.

purview

list[int] – The purview over which this mechanism’s $$\alpha$$ is maximal.

mip

AcMip – The minimum information partition for this mechanism.

unorderable_unless_eq = ['direction']
order_by()
__bool__()

An CausalLink is True if $$\alpha > 0$$.

to_json()

Return a JSON-serializable representation.

class pyphi.models.actual_causation.Event

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

actual_cause

CausalLink – The actual cause of the mechanism.

actual_effect

CausalLink – The actual effect of the mechanism.

Create new instance of Event(actual_cause, actual_effect)

mechanism

The mechanism of the event.

class pyphi.models.actual_causation.Account

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

irreducible_causes

The set of irreducible causes in this Account.

irreducible_effects

The set of irreducible effects in this Account.

to_json()
classmethod from_json(dct)
class pyphi.models.actual_causation.DirectedAccount

The set of CausalLink with $$\alpha > 0$$ for one direction of a transition.

class pyphi.models.actual_causation.AcBigMip(alpha=None, direction=None, unpartitioned_account=None, partitioned_account=None, transition=None, cut=None)

A minimum information partition for $$\mathcal{A}$$ calculation.

alpha

float – The $$\mathcal{A}$$ value for the transition when taken against this MIP, i.e. the difference between the unpartitioned account and this MIP’s partitioned account.

unpartitioned_account

Account – The account of the whole transition.

partitioned_account

Account – The account of the partitioned transition.

transition

Transition – The transition this MIP was calculated for.

cut

ActualCut – The minimal partition.

before_state

Return the actual past state of the Transition.

after_state

Return the actual current state of the Transition.

unorderable_unless_eq = ['direction']
order_by()
__bool__()

An AcBigMip is True if it has $$\mathcal{A} > 0$$.

to_json()