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- V = py.igl.eigen.MatrixXd();
- F = py.igl.eigen.MatrixXi();
- py.igl.read_triangle_mesh('../tutorial/shared/fertility.off', V, F);
- % Alternative discrete mean curvature
- HN = py.igl.eigen.MatrixXd();
- L = py.igl.eigen.SparseMatrixd();
- M = py.igl.eigen.SparseMatrixd();
- Minv = py.igl.eigen.SparseMatrixd();
- py.igl.cotmatrix(V,F,L)
- py.igl.massmatrix(V,F,py.igl.MASSMATRIX_TYPE_VORONOI,M)
- py.igl.invert_diag(M,Minv)
- % Laplace-Beltrami of position
- HN = -Minv*(L*V)
- % Extract magnitude as mean curvature
- H = HN.rowwiseNorm()
- % Compute curvature directions via quadric fitting
- PD1 = py.igl.eigen.MatrixXd()
- PD2 = py.igl.eigen.MatrixXd()
- PV1 = py.igl.eigen.MatrixXd()
- PV2 = py.igl.eigen.MatrixXd()
- py.igl.principal_curvature(V,F,PD1,PD2,PV1,PV2)
- % Mean curvature
- H = 0.5*(PV1+PV2)
- viewer = py.igl.viewer.Viewer()
- viewer.data.set_mesh(V, F)
- % Compute pseudocolor
- C = py.igl.eigen.MatrixXd()
- py.igl.parula(H,true,C)
- viewer.data.set_colors(C)
- % Average edge length for sizing
- avg = py.igl.avg_edge_length(V,F)
- % Draw a blue segment parallel to the minimal curvature direction
- red = py.iglhelpers.p2e(py.numpy.array([[0.8,0.2,0.2]]))
- blue = py.iglhelpers.p2e(py.numpy.array([[0.2,0.2,0.8]]))
- viewer.data.add_edges(V + PD1*avg, V - PD1*avg, blue)
- % Draw a red segment parallel to the maximal curvature direction
- viewer.data.add_edges(V + PD2*avg, V - PD2*avg, red)
- % Hide wireframe
- viewer.core.show_lines = false
- viewer.launch()
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