# models.mechanism¶

Mechanism-level objects.

class pyphi.models.mechanism.RepertoireIrreducibilityAnalysis(phi, direction, mechanism, purview, partition, repertoire, partitioned_repertoire, subsystem=None)

An analysis of the irreducibility ($$\varphi$$) of a mechanism over a purview, for a given partition, in one temporal direction.

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

phi

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

direction

DirectionCAUSE or EFFECT.

mechanism

tuple[int] – The mechanism that was analyzed.

purview

tuple[int] – The purview over which the the mechanism was analyzed.

partition

KPartition – The partition of the mechanism-purview pair that was analyzed.

repertoire

np.ndarray – The repertoire of the mechanism over the purview.

partitioned_repertoire

np.ndarray – The partitioned repertoire of the mechanism over the purview. This is the product of the repertoires of each part of the partition.

subsystem

Subsystem – The Subsystem the mechanism belongs to.

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

A RepertoireIrreducibilityAnalysis is True if it has $$\varphi > 0$$.

to_json()
class pyphi.models.mechanism.MaximallyIrreducibleCauseOrEffect(ria)

A maximally irreducible cause or effect (MICE).

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

phi

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

direction

DirectionCAUSE or EFFECT.

mechanism

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

purview

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

mip

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

repertoire

np.ndarray – The unpartitioned repertoire of the mechanism over the purview.

partitioned_repertoire

np.ndarray – The partitioned repertoire of the mechanism over the purview.

ria

RepertoireIrreducibilityAnalysis – The irreducibility analysis for this mechanism.

unorderable_unless_eq = ['direction']
order_by()
to_json()
damaged_by_cut(subsystem)

Return True if this MICE is affected by the subsystem’s cut.

The cut affects the MICE if it either splits the MICE’s mechanism or splits the connections between the purview and mechanism.

class pyphi.models.mechanism.MaximallyIrreducibleCause(ria)

A maximally irreducible cause (MIC).

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

direction

DirectionCAUSE.

class pyphi.models.mechanism.MaximallyIrreducibleEffect(ria)

A maximally irreducible effect (MIE).

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

direction

DirectionEFFECT.

class pyphi.models.mechanism.Concept(mechanism=None, cause=None, effect=None, subsystem=None, time=None)

The maximally irreducible cause and effect specified by a mechanism.

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

mechanism

tuple[int] – The mechanism that the concept consists of.

cause

MaximallyIrreducibleCause – The MaximallyIrreducibleCause representing the maximally-irreducible cause of this concept.

effect

MaximallyIrreducibleEffect – The MaximallyIrreducibleEffect representing the maximally-irreducible effect of this concept.

subsystem

Subsystem – This concept’s parent subsystem.

time

float – The number of seconds it took to calculate.

phi

float – The size of the concept.

This is the minimum of the $$\varphi$$ values of the concept’s MaximallyIrreducibleCause and MaximallyIrreducibleEffect.

cause_purview

tuple[int] – The cause purview.

effect_purview

tuple[int] – The effect purview.

cause_repertoire

np.ndarray – The cause repertoire.

effect_repertoire

np.ndarray – The effect repertoire.

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

A concept is True if $$\varphi > 0$$.

eq_repertoires(other)

Return whether this concept has the same repertoires as another.

Warning

This only checks if the cause and effect repertoires are equal as arrays; mechanisms, purviews, or even the nodes that the mechanism and purview indices refer to, might be different.

emd_eq(other)

Return whether this concept is equal to another in the context of an EMD calculation.

expand_cause_repertoire(new_purview=None)
expand_effect_repertoire(new_purview=None)
expand_partitioned_cause_repertoire()
expand_partitioned_effect_repertoire()
to_json()

Return a JSON-serializable representation.

classmethod from_json(dct)