def general_instances_test():
from solver.x_split_solver import SplitXSolver
from solver import MscColoringSolver
from create_gen_instances_script import create_random_instance
from database import TaskJobs
solver_x = SplitXSolver()
solver_c = MscColoringSolver()
jobs = []
for i in tqdm.trange(7, 20, desc="Vertices"):
for j in tqdm.trange(3,10, desc="Edge probability"):
for k in tqdm.trange(3, desc="Repetition"):
g = create_random_instance(i, edge_chance=0.1*j)
g.id = i*100+j*10+k
sol_x = solver_x.solve(g)
sol_c = solver_c.solve(g)
try:
assert sol_x.makespan < max(get_lower_bounds(g)) * 5.5 * math.ceil(math.log2(g.vert_amount))
assert sol_c.makespan < max(get_lower_bounds(g)) * 5.5 * math.ceil(math.log2(g.vert_amount))
except AssertionError as e:
print("Solution x-split:", sol_x.makespan, max(get_lower_bounds(g)) * 5.5 * math.ceil(math.log2(g.vert_amount)), "time:", sol_x.runtime)
print("Solution color:", sol_c.makespan, max(get_lower_bounds(g)) * 5.5 * math.ceil(math.log2(g.vert_amount)), "time:", sol_x.runtime)
raise e
jobs.append(TaskJobs(task=None, solution=sol_x, graph=g))
jobs.append(TaskJobs(task=None, solution=sol_c, graph=g))
from utils.visualization import visualize_solution_scatter, VisTypes
visualize_solution_scatter(jobs, "Bla", vis_type=VisTypes.LB_Runtime, logscale=True, loc=9)
def _create_task(arg_config, session):
solvers = arg_config.solvers
solvers_args = arg_config.solvers_args
assert len(solvers) == len(solvers_args),\
"The amount of solver arguments must match the amount of solvers"
for solver in solvers:
assert solver in ALL_SOLVER,\
f"Solver {solver} not found! Please make sure that all solver are properly named."
task = Task(task_type="instance_test", status=Task.STATUS_OPTIONS.CREATED, name=arg_config.name)
config = ConfigHolder.fromNamespace(arg_config, task=task,
ignored_attributes=["url_path", "solvers", "solvers_args", "create_only", "config", "name"])
jobs = _get_instances(task, config, session)
for solver, solver_args in zip(solvers, solvers_args):
subtask = Task(parent=task, name=f"{solver}_test", task_type="instance_test", status=Task.STATUS_OPTIONS.CREATED)
task.children.append(subtask)
subconfig_namespace = configargparse.Namespace(solver=solver,
solver_args=solver_args)
subconfig = ConfigHolder.fromNamespace(subconfig_namespace, task=subtask)
add_prev_job = (subconfig.with_start_sol is not None and subconfig.with_start_sol)
if isinstance(jobs[0], TaskJobs):
for task_job in jobs:
prev_job = task_job if add_prev_job else None
for i in range(config.repetitions):
subtask.jobs.append(TaskJobs(task=subtask, graph=task_job.graph, prev_job=prev_job))
else:
for graph in jobs:
for i in range(config.repetitions):
subtask.jobs.append(TaskJobs(task=subtask, graph=graph))
session.add(task)
session.commit()
return task, config
def main():
config = _load_config()
session = get_session(config.url_path)
graphs = []
if config.seed is None:
seed = int(np.random.default_rng(None).integers(np.array([2**63]))[0])
config.seed = seed
else:
seed = int(config.seed)
gen = np.random.default_rng(seed)
counter = 0
assert len(config.vertex_shape) % 2 == 0
shapes = np.array(config.vertex_shape).reshape(round(len(config.vertex_shape)/2), 2)
l_shapes = len(shapes)
for n in range(config.min_n, config.max_n):
size = config.cel_min
while size <= config.cel_max:
for i in range(config.repetitions):
graphs.append(create_random_celest_graph(n,vertex_shape=shapes[counter % l_shapes], celest_bounds=(size,size+config.cel_range), seed=gen))
counter += 1
size += config.cel_step
task = Task(name=config.name, task_type="CelestialGraphInstances", status=Task.STATUS_OPTIONS.FINISHED)
# Convert the namespace config into database config
task_config_holder = ConfigHolder.fromNamespace(config, task=task, ignored_attributes=["url_path", "name", "config"])
task.jobs = [TaskJobs(graph=graph, task=task) for graph in graphs]
session.add(task)
session.commit()
print(counter, "instances were created. Corresponding task is", task.id)
def main():
config = _load_config()
session = get_session(config.url_path)
if config.seed is None:
seed = int(np.random.default_rng(None).integers(np.array([2**63]))[0])
config.seed = seed
else:
seed = int(config.seed)
gen = np.random.default_rng(seed)
if config.fixed_edges:
graphs = _fixed_generation(config, gen)
else:
graphs = _probability_generation(config, gen)
task = Task(name=config.name,
task_type="GeometricGraphInstances",
status=Task.STATUS_OPTIONS.FINISHED)
# Convert the namespace config into database config
task_config_holder = ConfigHolder.fromNamespace(
config, task=task, ignored_attributes=["url_path", "name", "config"])
task.jobs = [TaskJobs(graph=graph, task=task) for graph in graphs]
session.add(task)
session.commit()
print(len(task.jobs), "instances were created. Corresponding task is",
task.id)
def _greedy_evolver_test(arg_config):
session = get_session(arg_config.url_path) if arg_config.url_path else None
task, config = _get_task_and_config(session, arg_config)
from angular_evolver.edge_order_evolver import create_circle_n_k
for n in range(config.min_n, config.max_n):
for k in range(config.min_k, min(config.max_k, math.floor(n / 2) + 1)):
graph = create_circle_n_k(n, k)
job = TaskJobs(task=task, graph=graph)
task.jobs.append(job)
session.commit()
if not arg_config.create_only:
process_task(config, task, session)