Files
igl/python/matlab/CurvatureDirections.m
T

60 lines
1.4 KiB
Matlab
Executable File

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()