def test_diag_indices():
di = diag_indices(4)
a = np.array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12],
[13, 14, 15, 16]])
a[di] = 100
assert_array_equal(
a, np.array([[100, 2, 3, 4],
[5, 100, 7, 8],
[9, 10, 100, 12],
[13, 14, 15, 100]])
)
# Now, we create indices to manipulate a 3-d array:
d3 = diag_indices(2, 3)
# And use it to set the diagonal of a zeros array to 1:
a = np.zeros((2, 2, 2), int)
a[d3] = 1
assert_array_equal(
a, np.array([[[1, 0],
[0, 0]],
[[0, 0],
[0, 1]]])
)
def test_diag_indices():
di = diag_indices(4)
a = np.array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12],
[13, 14, 15, 16]])
a[di] = 100
assert_array_equal(
a, np.array([[100, 2, 3, 4],
[5, 100, 7, 8],
[9, 10, 100, 12],
[13, 14, 15, 100]])
)
# Now, we create indices to manipulate a 3-d array:
d3 = diag_indices(2, 3)
# And use it to set the diagonal of a zeros array to 1:
a = np.zeros((2, 2, 2), int)
a[d3] = 1
assert_array_equal(
a, np.array([[[1, 0],
[0, 0]],
[[0, 0],
[0, 1]]])
)
def test_mesh_laplacian():
td = get_testdir()
s = Surface(op.join(td, 'in.surf.gii'))
try:
s.mesh_laplacian(-1)
except Exception as e:
assert isinstance(
e, ValueError), 'negative distance weight should give ValueError'
for w in range(4):
lap = s.mesh_laplacian(distance_weight=w)
assert (lap[np.diag_indices(lap.shape[0])] <
0).min(), 'positive diagonal'
outs = Surface(op.join(td, 'out.surf.gii'))
spc = toblerone.ImageSpace(op.join(td, 'ref.nii.gz'))
hemi = toblerone.Hemisphere(s, outs, 'L')
hemi2 = toblerone.Hemisphere(s, outs, 'R')
proj = toblerone.projection.Projector([hemi, hemi2], spc)
for w in range(4):
lap = proj.mesh_laplacian(w)
n = proj.hemi_dict['L'].n_points
assert not slice_sparse(lap, slice(0, n), slice(n, 2 * n)).nnz
assert not slice_sparse(lap, slice(n, 2 * n), slice(0, n)).nnz
assert not (lap[diag_indices(2 * n)] > 0).any()
