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- import sys, os
- # Add the igl library to the modules search path
- sys.path.insert(0, os.getcwd() + "/../")
- import pyigl as igl
- from shared import TUTORIAL_SHARED_PATH, check_dependencies
- dependencies = ["viewer"]
- check_dependencies(dependencies)
- 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)
- # Mean curvature
- H = 0.5 * (PV1 + PV2)
- viewer = igl.viewer.Viewer()
- viewer.data.set_mesh(V, F)
- # Compute pseudocolor
- C = igl.eigen.MatrixXd()
- igl.parula(H, True, C)
- viewer.data.set_colors(C)
- # Average edge length for sizing
- avg = igl.avg_edge_length(V, F)
- # Draw a blue segment parallel to the minimal curvature direction
- red = igl.eigen.MatrixXd([[0.8, 0.2, 0.2]])
- blue = igl.eigen.MatrixXd([[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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