def test_load_uniform_ball_cloud():
for n_points in [10, 20, 40, 80, 160]:
with warnings.catch_warnings(record=True) as w:
points = surface._load_uniform_ball_cloud(n_points=n_points)
assert_array_equal(points.shape, (n_points, 3))
assert_equal(len(w), 0)
assert_warns(surface.EfficiencyWarning,
surface._load_uniform_ball_cloud, n_points=3)
for n_points in [3, 10, 20]:
computed = surface._uniform_ball_cloud(n_points)
loaded = surface._load_uniform_ball_cloud(n_points)
assert_array_almost_equal(computed, loaded)
def test_load_uniform_ball_cloud():
for n_points in [10, 20, 40, 80, 160]:
with warnings.catch_warnings(record=True) as w:
points = surface._load_uniform_ball_cloud(n_points=n_points)
assert_array_equal(points.shape, (n_points, 3))
assert_equal(len(w), 0)
assert_warns(surface.EfficiencyWarning,
surface._load_uniform_ball_cloud, n_points=3)
# before 0.18 k-means was computed differently, so the result
# would differ from the stored values, computed with version 0.2
if LooseVersion(sklearn.__version__) >= LooseVersion('0.18'):
for n_points in [3, 10, 20]:
computed = surface._uniform_ball_cloud(n_points)
loaded = surface._load_uniform_ball_cloud(n_points)
assert_array_almost_equal(computed, loaded)
def test_sample_locations():
# check positions of samples on toy example, with an affine != identity
# flat horizontal mesh
mesh = flat_mesh(5, 7)
affine = np.diagflat([10, 20, 30, 1])
inv_affine = np.linalg.inv(affine)
# transform vertices to world space
vertices = np.asarray(
resampling.coord_transform(*mesh[0].T, affine=affine)).T
# compute by hand the true offsets in voxel space
# (transformed by affine^-1)
ball_offsets = surface._load_uniform_ball_cloud(10)
ball_offsets = np.asarray(
resampling.coord_transform(*ball_offsets.T, affine=inv_affine)).T
line_offsets = np.zeros((10, 3))
line_offsets[:, 2] = np.linspace(1, -1, 10)
line_offsets = np.asarray(
resampling.coord_transform(*line_offsets.T, affine=inv_affine)).T
# check we get the same locations
for kind, offsets in [('line', line_offsets), ('ball', ball_offsets)]:
locations = surface._sample_locations(
[vertices, mesh[1]], affine, 1., kind=kind, n_points=10)
true_locations = np.asarray([vertex + offsets for vertex in mesh[0]])
assert_array_equal(locations.shape, true_locations.shape)
assert_array_almost_equal(true_locations, locations)
pytest.raises(ValueError, surface._sample_locations,
mesh, affine, 1., kind='bad_kind')
def test_load_uniform_ball_cloud():
for n_points in [10, 20, 40, 80, 160]:
with warnings.catch_warnings(record=True) as w:
points = surface._load_uniform_ball_cloud(n_points=n_points)
assert_array_equal(points.shape, (n_points, 3))
assert_equal(len(w), 0)
assert_warns(surface.EfficiencyWarning,
surface._load_uniform_ball_cloud,
n_points=3)
# before 0.18 k-means was computed differently, so the result
# would differ from the stored values, computed with version 0.2
if LooseVersion(sklearn.__version__) >= LooseVersion('0.18'):
for n_points in [3, 10, 20]:
computed = surface._uniform_ball_cloud(n_points)
loaded = surface._load_uniform_ball_cloud(n_points)
assert_array_almost_equal(computed, loaded)
def test_sample_locations():
# check positions of samples on toy example, with an affine != identity
# flat horizontal mesh
mesh = flat_mesh(5, 7)
affine = np.diagflat([10, 20, 30, 1])
inv_affine = np.linalg.inv(affine)
# transform vertices to world space
vertices = np.asarray(
resampling.coord_transform(*mesh[0].T, affine=affine)).T
# compute by hand the true offsets in voxel space
# (transformed by affine^-1)
ball_offsets = surface._load_uniform_ball_cloud(10)
ball_offsets = np.asarray(
resampling.coord_transform(*ball_offsets.T, affine=inv_affine)).T
line_offsets = np.zeros((10, 3))
line_offsets[:, 2] = np.linspace(-1, 1, 10)
line_offsets = np.asarray(
resampling.coord_transform(*line_offsets.T, affine=inv_affine)).T
# check we get the same locations
for kind, offsets in [('line', line_offsets), ('ball', ball_offsets)]:
locations = surface._sample_locations(
[vertices, mesh[1]], affine, 1., kind=kind, n_points=10)
true_locations = np.asarray([vertex + offsets for vertex in mesh[0]])
assert_array_equal(locations.shape, true_locations.shape)
assert_array_almost_equal(true_locations, locations)
assert_raises(ValueError, surface._sample_locations,
mesh, affine, 1., kind='bad_kind')
def test_load_uniform_ball_cloud():
# Note: computed and shipped point clouds may differ since KMeans results
# change after
# https://github.com/scikit-learn/scikit-learn/pull/9288
# but the exact position of the points does not matter as long as they are
# well spread inside the unit ball
for n_points in [10, 20, 40, 80, 160]:
with warnings.catch_warnings(record=True) as w:
points = surface._load_uniform_ball_cloud(n_points=n_points)
assert_array_equal(points.shape, (n_points, 3))
assert len(w) == 0
with pytest.warns(surface.EfficiencyWarning):
surface._load_uniform_ball_cloud(n_points=3)
for n_points in [3, 7]:
computed = surface._uniform_ball_cloud(n_points)
loaded = surface._load_uniform_ball_cloud(n_points)
assert_array_almost_equal(computed, loaded)
assert (np.std(computed, axis=0) > .1).all()
assert (np.linalg.norm(computed, axis=1) <= 1).all()