# models.big_phi¶

Objects that represent cause-effect structures.

class pyphi.models.big_phi.BigMip(phi=None, unpartitioned_constellation=None, partitioned_constellation=None, subsystem=None, cut_subsystem=None, time=None, small_phi_time=None)

A minimum information partition for $$\Phi$$ calculation.

These can be compared with the built-in Python comparison operators (<, >, etc.). First, $$\Phi$$ values are compared. Then, if these are equal up to PRECISION, the one with the larger subsystem is greater.

phi

float – The $$\Phi$$ value for the subsystem when taken against this MIP, i.e. the difference between the unpartitioned constellation and this MIP’s partitioned constellation.

unpartitioned_constellation

Constellation – The constellation of the whole subsystem.

partitioned_constellation

Constellation – The constellation when the subsystem is cut.

subsystem

Subsystem – The subsystem this MIP was calculated for.

cut_subsystem

Subsystem – The subsystem with the minimal cut applied.

time

float – The number of seconds it took to calculate.

small_phi_time

float – The number of seconds it took to calculate the unpartitioned constellation.

print(constellations=True)

Print this BigMip, optionally without constellations.

cut

The unidirectional cut that makes the least difference to the subsystem.

network

The network this BigMip belongs to.

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

A BigMip is True if it has $$\Phi > 0$$.

to_json()

Return a JSON-serializable representation.