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.
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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 toPRECISION
, the size of the mechanism is compared.-
alpha
¶ float – This is the difference between the mechanism’s unpartitioned and partitioned actual probability.
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state
¶ tuple[int] – state of system in specified direction (past, future)
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direction
¶ str – The temporal direction specifiying whether this AcMIP should be calculated with cause or effect repertoires.
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mechanism
¶ tuple[int] – The mechanism over which to evaluate the AcMIP.
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purview
¶ tuple[int] – The purview over which the unpartitioned actual probability differs the least from the actual probability of the partition.
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partition
¶ tuple[Part, Part] – The partition that makes the least difference to the mechanism’s repertoire.
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probability
¶ float – The probability of the state in the past/future.
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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)
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unorderable_unless_eq
= ['direction']¶
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order_by
()¶
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phi
¶ Alias for \(\alpha\) for PyPhi utility functions.
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to_json
()¶ Return a JSON-serializable representation.
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class
pyphi.models.actual_causation.
CausalLink
(mip)¶ 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 toPRECISION
, the size of the mechanism is compared.-
alpha
¶ float – The difference between the mechanism’s unpartitioned and partitioned actual probabilities.
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phi
¶ Alias for \(\alpha\) for PyPhi utility functions.
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mechanism
¶ list[int] – The mechanism for which the action is evaluated.
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purview
¶ list[int] – The purview over which this mechanism’s \(\alpha\) is maximal.
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mip
¶ AcMip – The minimum information partition for this mechanism.
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unorderable_unless_eq
= ['direction']¶
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order_by
()¶
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__bool__
()¶ An
CausalLink
isTrue
if \(\alpha > 0\).
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to_json
()¶ Return a JSON-serializable representation.
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class
pyphi.models.actual_causation.
Event
¶ A mechanism which has both an actual cause and an actual effect.
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actual_cause
¶ CausalLink – The actual cause of the mechanism.
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actual_effect
¶ CausalLink – The actual effect of the mechanism.
Create new instance of Event(actual_cause, actual_effect)
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mechanism
¶ The mechanism of the event.
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class
pyphi.models.actual_causation.
Account
¶ The set of
CausalLink
with \(\alpha > 0\). This includes both actual causes and actual effects.-
to_json
()¶
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classmethod
from_json
(dct)¶
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class
pyphi.models.actual_causation.
DirectedAccount
¶ The set of
CausalLink
with \(\alpha > 0\) for one direction of a transition.
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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.
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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.
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unpartitioned_account
¶ Account – The account of the whole transition.
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partitioned_account
¶ Account – The account of the partitioned transition.
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transition
¶ Transition – The transition this MIP was calculated for.
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cut
¶ ActualCut – The minimal partition.
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before_state
¶ Return the actual past state of the
Transition
.
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after_state
¶ Return the actual current state of the
Transition
.
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unorderable_unless_eq
= ['direction']¶
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order_by
()¶
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to_json
()¶
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