Esempio n. 1
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    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, )
Esempio n. 2
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    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, )