def test_projection_matrix():
mesh = flat_mesh(5, 7, 4)
img = z_const_img(5, 7, 13)
proj = surface._projection_matrix(
mesh, np.eye(4), img.shape, radius=2., n_points=10)
# proj matrix has shape (n_vertices, img_size)
assert proj.shape == (5 * 7, 5 * 7 * 13)
# proj.dot(img) should give the values of img at the vertices' locations
values = proj.dot(img.ravel()).reshape((5, 7))
assert_array_almost_equal(values, img[:, :, 0])
mesh = flat_mesh(5, 7)
proj = surface._projection_matrix(
mesh, np.eye(4), (5, 7, 1), radius=.1, n_points=10)
assert_array_almost_equal(proj.toarray(), np.eye(proj.shape[0]))
mask = np.ones(img.shape, dtype=int)
mask[0] = 0
proj = surface._projection_matrix(
mesh, np.eye(4), img.shape, radius=2., n_points=10, mask=mask)
proj = proj.toarray()
# first row of the mesh is masked
assert_array_almost_equal(proj.sum(axis=1)[:7], np.zeros(7))
assert_array_almost_equal(proj.sum(axis=1)[7:], np.ones(proj.shape[0] - 7))
# mask and img should have the same shape
pytest.raises(ValueError, surface._projection_matrix,
mesh, np.eye(4), img.shape, mask=np.ones((3, 3, 2)))
def test_projection_matrix():
mesh = flat_mesh(5, 7, 4)
img = z_const_img(5, 7, 13)
proj = surface._projection_matrix(
mesh, np.eye(4), img.shape, radius=2., n_points=10)
# proj matrix has shape (n_vertices, img_size)
assert_equal(proj.shape, (5 * 7, 5 * 7 * 13))
# proj.dot(img) should give the values of img at the vertices' locations
values = proj.dot(img.ravel()).reshape((5, 7))
assert_array_almost_equal(values, img[:, :, 0])
mesh = flat_mesh(5, 7)
proj = surface._projection_matrix(
mesh, np.eye(4), (5, 7, 1), radius=.1, n_points=10)
assert_array_almost_equal(proj.toarray(), np.eye(proj.shape[0]))
mask = np.ones(img.shape, dtype=int)
mask[0] = 0
proj = surface._projection_matrix(
mesh, np.eye(4), img.shape, radius=2., n_points=10, mask=mask)
proj = proj.toarray()
# first row of the mesh is masked
assert_array_almost_equal(proj.sum(axis=1)[:7], np.zeros(7))
assert_array_almost_equal(proj.sum(axis=1)[7:], np.ones(proj.shape[0] - 7))
# mask and img should have the same shape
assert_raises(ValueError, surface._projection_matrix,
mesh, np.eye(4), img.shape, mask=np.ones((3, 3, 2)))
def test_sampling():
mesh = flat_mesh(5, 7, 4)
img = z_const_img(5, 7, 13)
mask = np.ones(img.shape, dtype=int)
mask[0] = 0
projectors = [
surface._nearest_voxel_sampling, surface._interpolation_sampling
]
for kind in ('line', 'ball'):
for projector in projectors:
projection = projector([img],
mesh,
np.eye(4),
kind=kind,
radius=0.)
assert_array_almost_equal(projection.ravel(), img[:, :, 0].ravel())
projection = projector([img],
mesh,
np.eye(4),
kind=kind,
radius=0.,
mask=mask)
assert_array_almost_equal(projection.ravel()[7:], img[1:, :,
0].ravel())
assert np.isnan(projection.ravel()[:7]).all()
def test_sampling(kind, use_inner_mesh, projection):
mesh = flat_mesh(5, 7, 4)
img = z_const_img(5, 7, 13)
mask = np.ones(img.shape, dtype=int)
mask[0] = 0
projector = {
"nearest": surface._nearest_voxel_sampling,
"linear": surface._interpolation_sampling
}[projection]
inner_mesh = mesh if use_inner_mesh else None
projection = projector([img],
mesh,
np.eye(4),
kind=kind,
radius=0.,
inner_mesh=inner_mesh)
assert_array_almost_equal(projection.ravel(), img[:, :, 0].ravel())
projection = projector([img],
mesh,
np.eye(4),
kind=kind,
radius=0.,
mask=mask,
inner_mesh=inner_mesh)
assert_array_almost_equal(projection.ravel()[7:], img[1:, :, 0].ravel())
assert np.isnan(projection.ravel()[:7]).all()
def test_sampling_between_surfaces(projection):
projector = {"nearest": surface._nearest_voxel_sampling,
"linear": surface._interpolation_sampling}[projection]
mesh = flat_mesh(13, 7, 3.)
inner_mesh = flat_mesh(13, 7, 1)
img = z_const_img(5, 7, 13).T
projection = projector(
[img], mesh, np.eye(4),
kind="auto", n_points=100, inner_mesh=inner_mesh)
assert_array_almost_equal(
projection.ravel(), img[:, :, 1:4].mean(axis=-1).ravel())
def test_sampling():
mesh = flat_mesh(5, 7, 4)
img = z_const_img(5, 7, 13)
mask = np.ones(img.shape, dtype=int)
mask[0] = 0
projectors = [surface._nearest_voxel_sampling,
surface._interpolation_sampling]
for kind in ('line', 'ball'):
for projector in projectors:
projection = projector([img], mesh, np.eye(4),
kind=kind, radius=0.)
assert_array_almost_equal(projection.ravel(), img[:, :, 0].ravel())
projection = projector([img], mesh, np.eye(4),
kind=kind, radius=0., mask=mask)
assert_array_almost_equal(projection.ravel()[7:],
img[1:, :, 0].ravel())
assert_true(np.isnan(projection.ravel()[:7]).all())