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Original file line number Diff line number Diff line change
Expand Up @@ -460,6 +460,8 @@ def get_element_gradient_for_location(
T[:, 1, 2] = 1 - local_coords[:, 0]
T[:, 1, 3] = local_coords[:, 0]

T[:, 0, :] /= self.step_vector[None, 0]
T[:, 1, :] /= self.step_vector[None, 1]
return vertices, T, elements, inside

def get_element_for_location(
Expand Down
41 changes: 41 additions & 0 deletions tests/unit/interpolator/test_2d_discrete_support.py
Original file line number Diff line number Diff line change
Expand Up @@ -80,3 +80,44 @@ def test_structured_grid2d_vtk_assigns_quad_cell_types():
triangulated = vtk_grid.triangulate()

assert triangulated.n_cells == grid.n_elements * 2


def test_evaluate_gradient_2d_world_units():
"""
Gradient must be returned in world units, independent of the cell size.

Regression test for #289: get_element_gradient_for_location returned the
shape-function derivatives with respect to local (0-1) cell coordinates,
so gradients were inflated by step_vector on each axis.
"""
grid = StructuredGrid2D(
origin=np.zeros(2), nsteps=np.array([10, 10]), step_vector=np.array([2.5, 0.5])
)
# f(x, y) = x and f(x, y) = y have unit gradients regardless of cell size
gradient_x = np.mean(grid.evaluate_gradient(grid.barycentre, grid.nodes[:, 0]), axis=0)
gradient_y = np.mean(grid.evaluate_gradient(grid.barycentre, grid.nodes[:, 1]), axis=0)
assert np.allclose(gradient_x, np.array([1.0, 0.0]))
assert np.allclose(gradient_y, np.array([0.0, 1.0]))


def test_fdi_2d_gradient_resolution_independent():
"""
The interpolated gradient magnitude must not depend on nelements (#289).
"""
from LoopStructural.geometry import BoundingBox
from LoopStructural.interpolators import InterpolatorFactory

sqrt2 = np.sqrt(2.0)
bbox = BoundingBox(dimensions=2, origin=np.array([0.0, 0.0]), maximum=np.array([100.0, 100.0]))
points = np.random.default_rng(0).uniform(10, 90, size=(60, 2))
for nelements in (1e3, 4e3):
interpolator = InterpolatorFactory.create_interpolator(
interpolatortype="FDI", boundingbox=bbox, nelements=nelements
)
interpolator.set_value_constraints(
np.column_stack([points, (points[:, 0] + points[:, 1]) / sqrt2])
)
interpolator.setup_interpolator()
interpolator.solve_system(solver="cg")
gradient_norm = np.linalg.norm(interpolator.evaluate_gradient(np.array([[50.0, 50.0]]))[0])
assert np.isclose(gradient_norm, 1.0, atol=0.05)
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