def test_custom_centroids(use_kd_tree):
centroids = np.array([[-0.25, -0.25], [0.25, 0.25]])
archive = CVTArchive(centroids.shape[0], [(-1, 1), (-1, 1)],
custom_centroids=centroids,
use_kd_tree=use_kd_tree)
archive.initialize(solution_dim=3)
assert archive.samples is None
assert (archive.centroids == centroids).all()
def _cvt_archive():
"""Deterministically created CVTArchive."""
archive = CVTArchive(100, [(-1, 1), (-1, 1)],
samples=1000,
use_kd_tree=True,
seed=42)
archive.initialize(solution_dim=2)
_add_uniform_sphere(archive, (-1, 1), (-1, 1))
return archive
def _long_cvt_archive():
"""Same as above, but the behavior space is longer in one direction."""
archive = CVTArchive(100, [(-2, 2), (-1, 1)],
samples=1000,
use_kd_tree=True,
seed=42)
archive.initialize(solution_dim=2)
_add_uniform_sphere(archive, (-2, 2), (-1, 1))
return archive
def setup():
archive = CVTArchive(1000, [(-1, 1), (-1, 1)],
samples=20_000,
use_kd_tree=use_kd_tree)
archive.initialize(solutions.shape[1])
# Let numba compile.
archive.add(solutions[0], objective_values[0], behavior_values[0])
return (archive,), {}
def benchmark_get_10k_random_elites(use_kd_tree, benchmark, benchmark_data_10k):
n, solutions, objective_values, behavior_values = benchmark_data_10k
archive = CVTArchive(1000, [(-1, 1), (-1, 1)],
samples=20_000,
use_kd_tree=use_kd_tree)
archive.initialize(solutions.shape[1])
for i in range(n):
archive.add(solutions[i], objective_values[i], behavior_values[i])
@benchmark
def get_elites():
for i in range(n):
sol, obj, beh = archive.get_random_elite()
def benchmark_as_pandas_2000_items(benchmark):
bins = 2000
archive = CVTArchive(bins, [(-1, 1), (-1, 1)],
use_kd_tree=True,
samples=50_000)
archive.initialize(10)
for x, y in archive.centroids:
sol = np.random.random(10)
sol[0] = x
sol[1] = y
archive.add(sol, 1.0, np.array([x, y]))
# Archive should be full.
assert len(archive.as_pandas()) == bins
benchmark(archive.as_pandas)
def init():
archive = CVTArchive(1000, [(-1, 1), (-1, 1)],
samples=20_000,
use_kd_tree=use_kd_tree)
archive.initialize(solution_dim=2)
def setup(bins, use_kd_tree):
nonlocal archive
archive = CVTArchive(bins, [(-1, 1), (-1, 1)],
custom_centroids=ref_archives[bins].centroids,
use_kd_tree=use_kd_tree)
archive.initialize(solutions.shape[1])