#Edges
e1 = E + Help(source=n8, target=n4)
e2 = E + Help(source=n9, target=n5)
e3 = E + Help(source=n9, target=n6)
e4 = E + And(source=n7, target=n9)
e5 = E + And(source=n8, target=n9)
e6 = E + Hurt(source=n14, target=n10)
e7 = E + Help(source=n14, target=n11)
e8 = E + Help(source=n13, target=n12)
e9 = E + Help(source=n15, target=n13)
e10 = E + Or(source=n14, target=n16)
e11 = E + Or(source=n15, target=n16)
graph = Graph(name="GardenBridge", nodes=N.all, edges=E.all)
if __name__ == "__main__":
from pystar.model import Model
from utilities.de import DE
from star1.star1 import run
run(graph, "miniature")
def test_star1():
from pystar.models.dot_models import modelers
from star1 import star1
for model in modelers:
star1.run(model())
def test_star1(model_name, show_optimal_index = True):
for model in modelers:
if model.__name__ == model_name:
optimal_index = optimal_indices.get(model_name, None) if show_optimal_index else None
star1.run(model(), SUB_FOLDER, optimal_index=optimal_index)
e2 = E + Hurt(source=n7, target=n1)
e3 = E + Hurt(source=n6, target=n2)
e4 = E + Or(source=n6, target=n4)
e5 = E + Or(source=n7, target=n4)
e6 = E + And(source=n3, target=n6)
e7 = E + And(source=n8, target=n6)
e8 = E + And(source=n9, target=n6)
e9 = E + And(source=n10, target=n6)
e10 = E + And(source=n11, target=n8)
e11 = E + And(source=n12, target=n10)
e12 = E + And(source=n5, target=n10)
graph = Graph(name="AmazonDrone", nodes=N.all, edges=E.all)
if __name__ == "__main__":
from pystar.model import Model
from utilities.de import DE
from star1.star1 import run
run(graph, "miniature")
def test_star1():
from pystar.models.dot_models import modelers
from star1 import star1
for model in modelers:
star1.run(model())
def test_star1(model_name, show_optimal_index=True):
for model in modelers:
if model.__name__ == model_name:
optimal_index = optimal_indices.get(
model_name, None) if show_optimal_index else None
star1.run(model(), SUB_FOLDER, optimal_index=optimal_index)
