def test_big_mip_single_node(s_single, flushcache, restore_fs_cache):
flushcache()
initial_option = constants.SINGLE_NODES_WITH_SELFLOOPS_HAVE_PHI
constants.SINGLE_NODES_WITH_SELFLOOPS_HAVE_PHI = True
assert compute.big_mip(s_single).phi == 0.5
constants.SINGLE_NODES_WITH_SELFLOOPS_HAVE_PHI = False
assert compute.big_mip(s_single).phi == 0.0
constants.SINGLE_NODES_WITH_SELFLOOPS_HAVE_PHI = initial_option
def test_big_mip_single_node(s_single, flushcache, restore_fs_cache):
flushcache()
initial_option = config.SINGLE_NODES_WITH_SELFLOOPS_HAVE_PHI
config.SINGLE_NODES_WITH_SELFLOOPS_HAVE_PHI = True
assert compute.big_mip(s_single).phi == 0.5
config.SINGLE_NODES_WITH_SELFLOOPS_HAVE_PHI = False
assert compute.big_mip(s_single).phi == 0.0
config.SINGLE_NODES_WITH_SELFLOOPS_HAVE_PHI = initial_option
def test_big_mip_wrappers(reducible, flushcache, restore_fs_cache):
flushcache()
assert (compute.big_mip(reducible) ==
models.BigMip(subsystem=reducible, cut_subsystem=reducible,
phi=0.0, unpartitioned_constellation=[],
partitioned_constellation=[]))
assert compute.big_phi(reducible) == 0.0
def test_big_mip_wrappers(reducible, flushcache, restore_fs_cache):
flushcache()
assert (compute.big_mip(reducible) ==
models.BigMip(subsystem=reducible, cut_subsystem=reducible,
phi=0.0, unpartitioned_constellation=[],
partitioned_constellation=[]))
assert compute.big_phi(reducible) == 0.0
def test_big_mip_empty_subsystem(s_empty, flushcache, restore_fs_cache):
flushcache()
assert (compute.big_mip(s_empty) ==
models.BigMip(phi=0.0,
unpartitioned_constellation=[],
partitioned_constellation=[],
subsystem=s_empty,
cut_subsystem=s_empty))
def test_big_mip_empty_subsystem(s_empty, flushcache, restore_fs_cache):
flushcache()
assert (compute.big_mip(s_empty) ==
models.BigMip(phi=0.0,
unpartitioned_constellation=(),
partitioned_constellation=(),
subsystem=s_empty,
cut_subsystem=s_empty))
def test_big_mip_standard_example_sequential(s, flushcache, restore_fs_cache):
flushcache()
initial = constants.PARALLEL_CUT_EVALUATION
constants.PARALLEL_CUT_EVALUATION = False
mip = compute.big_mip(s)
check_mip(mip, standard_answer)
constants.PARALLEL_CUT_EVALUATION = initial
def test_big_mip_standard_example_parallel(s, flushcache, restore_fs_cache):
flushcache()
initial = (constants.PARALLEL_CUT_EVALUATION, constants.NUMBER_OF_CORES)
constants.PARALLEL_CUT_EVALUATION, constants.NUMBER_OF_CORES = True, -2
mip = compute.big_mip(s)
check_mip(mip, standard_answer)
constants.PARALLEL_CUT_EVALUATION, constants.NUMBER_OF_CORES = initial
def test_expand_cause_repertoire(micro_s_all_off):
mip = big_mip(micro_s_all_off)
A = mip.unpartitioned_constellation[0]
cause = A.cause.mip.unpartitioned_repertoire
assert np.all(abs(A.expand_cause_repertoire(CD) - cause) < EPSILON)
assert np.all(abs(
A.expand_cause_repertoire(BCD).flatten(order='F') -
np.array([1/6 if i < 6 else 0 for i in range(8)])) < EPSILON)
assert np.all(abs(
A.expand_cause_repertoire(ABCD).flatten(order='F') -
np.array([1/12 if i < 12 else 0 for i in range(16)])) < EPSILON)
assert np.all(abs(A.expand_cause_repertoire(ABCD) -
A.expand_cause_repertoire()) < EPSILON)
def test_expand_effect_repertoire(micro_s_all_off):
mip = big_mip(micro_s_all_off)
A = mip.unpartitioned_constellation[0]
effect = A.effect.mip.unpartitioned_repertoire
assert np.all(abs(A.expand_effect_repertoire(CD) - effect) < EPSILON)
assert np.all(abs(A.expand_effect_repertoire(BCD).flatten(order='F') -
np.array([.25725, .23275, .11025, .09975,
.11025, .09975, .04725, .04275])) < EPSILON)
assert np.all(abs(
A.expand_effect_repertoire(ABCD).flatten(order='F') -
np.array([.13505625, .12219375, .12219375, .11055625,
.05788125, .05236875, .05236875, .04738125,
.05788125, .05236875, .05236875, .04738125,
.02480625, .02244375, .02244375, .02030625])) < EPSILON)
assert np.all(abs(A.expand_effect_repertoire(ABCD) -
A.expand_effect_repertoire()) < EPSILON)
def test_expand_cause_repertoire(micro_s_all_off):
mip = big_mip(micro_s_all_off)
A = mip.unpartitioned_constellation[0]
cause = A.cause.mip.unpartitioned_repertoire
assert np.all(abs(A.expand_cause_repertoire(CD) - cause) < EPSILON)
assert np.all(
abs(
A.expand_cause_repertoire(BCD).flatten(order='F') -
np.array([1 / 6 if i < 6 else 0 for i in range(8)])) < EPSILON)
assert np.all(
abs(
A.expand_cause_repertoire(ABCD).flatten(order='F') -
np.array([1 / 12 if i < 12 else 0 for i in range(16)])) < EPSILON)
assert np.all(
abs(A.expand_cause_repertoire(ABCD) -
A.expand_cause_repertoire()) < EPSILON)
def test_expand_effect_repertoire(micro_s_all_off):
mip = big_mip(micro_s_all_off)
A = mip.unpartitioned_constellation[0]
effect = A.effect.mip.unpartitioned_repertoire
assert np.all(abs(A.expand_effect_repertoire(CD) - effect) < EPSILON)
assert np.all(
abs(
A.expand_effect_repertoire(BCD).flatten(order='F') - np.array([
.25725, .23275, .11025, .09975, .11025, .09975, .04725, .04275
])) < EPSILON)
assert np.all(
abs(
A.expand_effect_repertoire(ABCD).flatten(order='F') - np.array([
.13505625, .12219375, .12219375, .11055625, .05788125,
.05236875, .05236875, .04738125, .05788125, .05236875,
.05236875, .04738125, .02480625, .02244375, .02244375,
.02030625
])) < EPSILON)
assert np.all(
abs(A.expand_effect_repertoire(ABCD) -
A.expand_effect_repertoire()) < EPSILON)
def test_big_mip_disconnected_network(reducible, flushcache, restore_fs_cache):
flushcache()
assert (compute.big_mip(reducible) ==
models.BigMip(subsystem=reducible, cut_subsystem=reducible,
phi=0.0, unpartitioned_constellation=[],
partitioned_constellation=[]))
def test_big_mip_complete_graph_standard_example(s_complete):
mip = compute.big_mip(s_complete)
check_mip(mip, standard_answer)
def test_big_mip_complete_graph_s_noised(s_noised_complete):
mip = compute.big_mip(s_noised_complete)
check_mip(mip, noised_answer)
def test_big_mip_complete_graph_standard_example(s_complete):
mip = compute.big_mip(s_complete)
check_mip(mip, standard_answer)
def test_big_mip_disconnected_network(reducible, flushcache, restore_fs_cache):
flushcache()
assert (compute.big_mip(reducible) ==
models.BigMip(subsystem=reducible, cut_subsystem=reducible,
phi=0.0, unpartitioned_constellation=[],
partitioned_constellation=[]))
def test_big_mip_complete_graph_big_subsys_all(big_subsys_all_complete):
mip = compute.big_mip(big_subsys_all_complete)
check_mip(mip, big_answer)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from pyphi.compute import big_mip
from pyphi import Subsystem
import numpy as np
import example_networks
from pyphi.constants import EPSILON
micro = example_networks.micro()
micro.current_state = (0, 0, 0, 0)
micro.past_state = (0, 0, 0, 0)
micro_subsystem = Subsystem(range(micro.size), micro)
mip = big_mip(micro_subsystem)
CD = micro_subsystem.nodes[2:4]
BCD = micro_subsystem.nodes[1:4]
ABCD = micro_subsystem.nodes[0:4]
A = mip.unpartitioned_constellation[0]
cause = A.cause.mip.unpartitioned_repertoire
effect = A.effect.mip.unpartitioned_repertoire
def test_expand_cause_repertoire():
assert np.all(abs(A.expand_cause_repertoire(CD) - cause) < EPSILON)
assert np.all(
abs(
A.expand_cause_repertoire(BCD).flatten(order='F') -
np.array([1 / 6 if i < 6 else 0 for i in range(8)])) < EPSILON)
def test_big_mip_macro(macro_s, flushcache, restore_fs_cache):
flushcache()
mip = compute.big_mip(macro_s)
check_mip(mip, macro_answer)
def test_big_mip_big_network_0_thru_3(big_subsys_0_thru_3, flushcache,
restore_fs_cache):
flushcache()
mip = compute.big_mip(big_subsys_0_thru_3)
check_mip(mip, big_subsys_0_thru_3_answer)
def test_big_mip_big_network(big_subsys_all, flushcache, restore_fs_cache):
flushcache()
mip = compute.big_mip(big_subsys_all)
check_mip(mip, big_answer)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from pyphi.compute import big_mip
from pyphi import Subsystem
import numpy as np
import example_networks
from pyphi.constants import EPSILON
micro = example_networks.micro()
micro.current_state = (0, 0, 0, 0)
micro.past_state = (0, 0, 0, 0)
micro_subsystem = Subsystem(range(micro.size), micro)
mip = big_mip(micro_subsystem)
CD = micro_subsystem.nodes[2:4]
BCD = micro_subsystem.nodes[1:4]
ABCD = micro_subsystem.nodes[0:4]
A = mip.unpartitioned_constellation[0]
cause = A.cause.mip.unpartitioned_repertoire
effect = A.effect.mip.unpartitioned_repertoire
def test_expand_cause_repertoire():
assert np.all(abs(A.expand_cause_repertoire(CD) - cause) < EPSILON)
assert np.all(abs(
A.expand_cause_repertoire(BCD).flatten(order='F') -
np.array([1/6 if i < 6 else 0 for i in range(8)])) < EPSILON)
assert np.all(abs(
def test_big_mip_big_network_0_thru_3(big_subsys_0_thru_3, flushcache,
restore_fs_cache):
flushcache()
mip = compute.big_mip(big_subsys_0_thru_3)
check_mip(mip, big_subsys_0_thru_3_answer)
def test_big_mip_complete_graph_rule152_s(rule152_s_complete):
mip = compute.big_mip(rule152_s_complete)
check_mip(mip, rule152_answer)
def test_big_mip_complete_graph_s_noised(s_noised_complete):
mip = compute.big_mip(s_noised_complete)
check_mip(mip, noised_answer)
def test_big_mip_complete_graph_rule152_s(rule152_s_complete):
mip = compute.big_mip(rule152_s_complete)
check_mip(mip, rule152_answer)
def test_big_mip_complete_graph_big_subsys_all(big_subsys_all_complete):
mip = compute.big_mip(big_subsys_all_complete)
check_mip(mip, big_answer)
def test_big_mip_rule152(rule152_s, flushcache, restore_fs_cache):
flushcache()
mip = compute.big_mip(rule152_s)
check_mip(mip, rule152_answer)
def test_big_mip_big_network(big_subsys_all, flushcache, restore_fs_cache):
flushcache()
mip = compute.big_mip(big_subsys_all)
check_mip(mip, big_answer)
def test_jsonify_big_mip(s, flushcache, restore_fs_cache):
flushcache()
jsonify.loads(jsonify.dumps(compute.big_mip(s)))
def test_big_mip_rule152(rule152_s, flushcache, restore_fs_cache):
flushcache()
mip = compute.big_mip(rule152_s)
check_mip(mip, rule152_answer)
def test_big_mip_single_node_selfloops_dont_have_phi(s_single, flushcache,
restore_fs_cache):
flushcache()
assert compute.big_mip(s_single).phi == 0.0
