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Fix NaNs in test_discrete_gradient on DOLFINx nightly #268

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Merged
finsberg merged 1 commit into from
Oct 12, 2026
Merged

Fix NaNs in test_discrete_gradient on DOLFINx nightly #268

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29 changes: 18 additions & 11 deletions tests/test_interpolation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -134,16 +134,23 @@ def test_discrete_gradient(degree, use_petsc, cell_type):

G_ref = dolfinx.fem.discrete_gradient(V, W)

# Built in matrices has to use a special input vector, with additional ghosts.
try:
_x = dolfinx.la.vector(G_ref.index_map(1), G_ref.block_size[1])
except AttributeError:
# Bug in DOLFINx 0.9.0
_x = dolfinx.la.vector(G_ref.index_map(1), G_ref.bs[1])

num_owned_dofs = V.dofmap.index_map.size_local * V.dofmap.index_map_bs
_x.array[:num_owned_dofs] = u.x.array[:num_owned_dofs]
_x.scatter_forward()

def input_vector(matrix):
"""`u` on the column index map of `matrix`, which `MatrixCSR.mult` indexes into.

The column map can have more ghosts than `V`'s, and two matrices on `V` need not
share one: on DOLFINx nightly, `discrete_gradient` uses `V`'s map while
`create_matrix` adds ghosts. A vector on another matrix's map is read out of bounds.
"""
try:
x = dolfinx.la.vector(matrix.index_map(1), matrix.block_size[1])
except AttributeError:
# Bug in DOLFINx 0.9.0
x = dolfinx.la.vector(matrix.index_map(1), matrix.bs[1])
x.array[:num_owned_dofs] = u.x.array[:num_owned_dofs]
x.scatter_forward()
return x

if use_petsc:
A = scifem.interpolation.petsc_interpolation_matrix(expr, W)
Expand All @@ -153,7 +160,7 @@ def test_discrete_gradient(degree, use_petsc, cell_type):
if not hasattr(dolfinx.la.MatrixCSR, "mult"):
pytest.skip("MatrixCSR has no mult method")
A = scifem.interpolation.interpolation_matrix(expr, W)
A.mult(_x, w.x)
A.mult(input_vector(A), w.x)
w.x.scatter_forward()

w_ref = dolfinx.fem.Function(W)
Expand All @@ -166,7 +173,7 @@ def test_discrete_gradient(degree, use_petsc, cell_type):
G_ref.assemble()
G_ref.mult(u.x.petsc_vec, w_ref.x.petsc_vec)
else:
G_ref.mult(_x, w_ref.x)
G_ref.mult(input_vector(G_ref), w_ref.x)
w_ref.x.scatter_forward()

np.testing.assert_allclose(w.x.array, w_ref.x.array, rtol=1e-11, atol=1e-12)
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