def test_default_scramble_strategy(self):
bn = template_behaviour_generator(5, 2, 0.5, 0.0, 1, 0).new()
bn_copy = BooleanNetwork.from_json(bn.to_json())
bn_copy, flips = bn_scramble_strategy(bn_copy, 1)
self.assertFalse(bn.to_json() == bn_copy.to_json())
bn_copy = edit_boolean_network(bn_copy, flips)
self.assertTrue(bn.to_json() == bn_copy.to_json())
def test_bn_update(self):
bn = template_behaviour_generator(5, 2, 0.5, 0.0, 1, 0).new()
bn_copy = BooleanNetwork.from_json(bn.to_json())
matching_states = []
for _ in range(10):
s1 = binstate(bn.update())
s2 = binstate(bn_copy.update())
matching_states.append(s1 == s2)
self.assertTrue(all(matching_states))
def test_bn_state_space_homogeneity(bn: BooleanNetwork, i: int,
noise_rho: float):
'''
Checks whether the attractor space is:
* Deaf to inputs values in presence of "ambient" noise.
That is, setting an input node state to a certain value
doesn't lock the trajectory of the BN to a single attractor.
* Displays, to some degree of alternance, all the attractors (see ATM).
'''
states = [bn.noisy_update(noise_rho) for _ in range(i)]
found_attrs = search_attractors(states, bn.atm.dattractors)
return len(set(found_attrs)) == len(bn.atm.attractors)
from pathlib import Path
from pandas import DataFrame
from pprint import pprint
from bncontroller.sim.utils import GLOBALS, load_global_config
from bncontroller.boolnet.selector import SelectiveBooleanNetwork
from bncontroller.boolnet.structures import BooleanNetwork
from bncontroller.jsonlib.utils import read_json
from bncontroller.filelib.utils import get_dir
if __name__ == "__main__":
load_global_config()
for path in get_dir(GLOBALS.bn_model_path).iterdir():
if path.is_file():
bn: BooleanNetwork = BooleanNetwork.from_json(read_json(path))
print(str(path))
print(DataFrame(bn.atm.dtableau).T)
print(bn.atm.tableau)
for k, a in bn.atm.dattractors.items():
print(k, a)
print(bn.atm.attractors)
def new(self) -> BooleanNetwork:
nodes = self.__connect_nodes(self.__build_nodes())
return BooleanNetwork(nodes)
def test_ebnf(self):
bn = template_behaviour_generator(5, 2, 0.5, 0.0, 1, 0).new()
bn_copy = BooleanNetwork.from_json(bn.to_json())
self.assertTrue(bn.to_ebnf(), bn_copy.to_ebnf())
def c2no1(bnname, c):
# bnname, c = cols
print(bnname)
bn = BooleanNetwork.from_json(
read_json(GLOBALS.bn_model_path / 'stats/models' / bnname))
return c if len(bn.atm.attractors) > 1 else False