igl.readOFF("../../tutorial/shared/cheburashka.off",V,F)
# Two fixed points
# Left hand, left foot
b = igl.eigen.MatrixXi([[4331],[5957]])
bc = igl.eigen.MatrixXd([[1],[-1]])
# Construct Laplacian and mass matrix
L = igl.eigen.SparseMatrixd()
M = igl.eigen.SparseMatrixd()
Minv = igl.eigen.SparseMatrixd()
Q = igl.eigen.SparseMatrixd()
igl.cotmatrix(V,F,L)
igl.massmatrix(V,F,igl.MASSMATRIX_TYPE_VORONOI,M)
igl.invert_diag(M,Minv)
# Bi-Laplacian
Q = L * (Minv * L);
# Zero linear term
B = igl.eigen.MatrixXd.Zero(V.rows(),1);
Z = igl.eigen.MatrixXd()
Z_const = igl.eigen.MatrixXd()
# Alternative, short hand
mqwf = igl.min_quad_with_fixed_data()
# Empty constraints
Beq = igl.eigen.MatrixXd()
V = igl.eigen.MatrixXd() F = igl.eigen.MatrixXi() igl.read_triangle_mesh(TUTORIAL_SHARED_PATH + "fertility.off", V, F) # Alternative discrete mean curvature HN = igl.eigen.MatrixXd() L = igl.eigen.SparseMatrixd() M = igl.eigen.SparseMatrixd() Minv = igl.eigen.SparseMatrixd() igl.cotmatrix(V, F, L) igl.massmatrix(V, F, igl.MASSMATRIX_TYPE_VORONOI, M) 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 = igl.eigen.MatrixXd() PD2 = igl.eigen.MatrixXd() PV1 = igl.eigen.MatrixXd() PV2 = igl.eigen.MatrixXd() igl.principal_curvature(V, F, PD1, PD2, PV1, PV2)
