def test_isosurface_non_orthogonal(self, setup):
pytest.importorskip("skimage", reason="scikit-image not available")
# If the grid is non-orthogonal, there should be 20 unique values
# (10 for each (HERE), see test_isosurface_orthogonal)
grid = Grid(0.1, sc=[[1, 0, 0], [0, 1, 0], [0, 2, 1]])
grid.grid = np.tile([1, 2, 3, 4, 5, 4, 3, 2, 1, 0],
100).reshape(10, 10, 10)
verts, *returns = grid.isosurface(2.5)
# we have twice as many since the 3rd lattice vector has components in y
assert np.unique(verts[:, 1]).shape == (20, )
assert np.unique(verts[:, 2]).shape == (2, )
def test_isosurface_orthogonal(self, setup):
pytest.importorskip("skimage", reason="scikit-image not available")
# Build an empty grid
grid = Grid(0.1, sc=[[1, 0, 0], [0, 1, 0], [0, 0, 1]])
# Fill it with some values that have a clear isosurface
grid.grid = np.tile([1, 2, 3, 4, 5, 4, 3, 2, 1, 0],
100).reshape(10, 10, 10)
# Calculate the isosurface for the value of 2.5
verts, *returns = grid.isosurface(2.5)
# The third dimension should contain only two coordinates
# [1, 2, (HERE) 3, 4, 5, 4, 3, (HERE) 2, 1, 0]
assert np.unique(verts[:, 1]).shape == (10, )
assert np.unique(verts[:, 2]).shape == (2, )
