def test_compute_from_network():
"""Tests the it works given an arbitrary network and lines.
"""
if not Network.has_connection():
pytest.skip("No server connected.")
network = Network([ReluLayer()])
lines = [(np.array([0.0, 1.0]), np.array([0.0, -1.0])),
(np.array([2.0, 3.0]), np.array([4.0, 3.0]))]
classifier = LinesClassifier(network, lines, preimages=True)
classifier.partial_compute()
exactlines = network.exactlines(lines, True, True)
assert all(
np.allclose(actual[0], truth[0]) and np.allclose(actual[1], truth[1])
for actual, truth in zip(classifier.transformed_lines, exactlines))
classified = classifier.compute()
assert len(classified) == len(lines)
regions, labels = classified[0]
assert np.allclose(regions,
[[[0.0, 1.0], [0.0, 0.0]], [[0.0, 0.0], [0.0, -1.0]]])
assert np.allclose(labels, [1, 0])
regions, labels = classified[1]
assert np.allclose(regions,
[[[2.0, 3.0], [3.0, 3.0]], [[3.0, 3.0], [4.0, 3.0]]])
assert np.allclose(labels, [1, 0])
# Ensure it doesn't re-compute things it already knows.
assert classifier.compute() is classified
def test_compute_from_exactlines():
"""Tests the it works given pre-transformed lines.
"""
if not Network.has_connection():
pytest.skip("No server connected.")
network = Network([ReluLayer()])
lines = [(np.array([0.0, 1.0]), np.array([0.0, -1.0])),
(np.array([2.0, 3.0]), np.array([4.0, 3.0]))]
exactlines = network.exactlines(lines, True, True)
classifier = LinesClassifier.from_exactlines(exactlines)
classified = classifier.compute()
assert len(classified) == len(lines)
regions, labels = classified[0]
assert np.allclose(regions,
[[[0.0, 1.0], [0.0, 0.0]], [[0.0, 0.0], [0.0, -1.0]]])
assert np.allclose(labels, [1, 0])
regions, labels = classified[1]
assert np.allclose(regions,
[[[2.0, 3.0], [3.0, 3.0]], [[3.0, 3.0], [4.0, 3.0]]])
assert np.allclose(labels, [1, 0])