78 lines
1.6 KiB
Python
78 lines
1.6 KiB
Python
# Add the igl library to the modules search path
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import sys, os
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sys.path.insert(0, os.getcwd() + "/../")
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import pyigl as igl
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V = igl.eigen.MatrixXd()
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F = igl.eigen.MatrixXi()
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igl.readOFF("../../tutorial/shared/camelhead.off",V,F)
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# Find boundary edges
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E = igl.eigen.MatrixXi()
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igl.boundary_facets(F,E);
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# Find boundary vertices
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b = igl.eigen.MatrixXi()
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IA = igl.eigen.MatrixXi()
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IC = igl.eigen.MatrixXi()
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igl.unique(E,b,IA,IC);
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# List of all vertex indices
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vall = igl.eigen.MatrixXi()
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vin = igl.eigen.MatrixXi()
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igl.coloni(0,V.rows()-1,vall)
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# List of interior indices
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igl.setdiff(vall,b,vin,IA)
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# Construct and slice up Laplacian
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L = igl.eigen.SparseMatrixd()
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L_in_in = igl.eigen.SparseMatrixd()
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L_in_b = igl.eigen.SparseMatrixd()
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igl.cotmatrix(V,F,L)
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igl.slice(L,vin,vin,L_in_in)
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igl.slice(L,vin,b,L_in_b)
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# Dirichlet boundary conditions from z-coordinate
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bc = igl.eigen.MatrixXd()
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Z = V.col(2)
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igl.slice(Z,b,bc)
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# Solve PDE
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solver = igl.eigen.SimplicialLLTsparse(-L_in_in)
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Z_in = solver.solve(L_in_b*bc)
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# slice into solution
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igl.slice_into(Z_in,vin,Z)
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# Alternative, short hand
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mqwf = igl.min_quad_with_fixed_data()
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# Linear term is 0
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B = igl.eigen.MatrixXd()
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B.setZero(V.rows(),1);
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# Empty constraints
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Beq = igl.eigen.MatrixXd()
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Aeq = igl.eigen.SparseMatrixd()
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# Our cotmatrix is _negative_ definite, so flip sign
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igl.min_quad_with_fixed_precompute(-L,b,Aeq,True,mqwf)
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igl.min_quad_with_fixed_solve(mqwf,B,bc,Beq,Z)
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# Pseudo-color based on solution
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C = igl.eigen.MatrixXd()
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igl.jet(Z,True,C)
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# Plot the mesh with pseudocolors
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viewer = igl.viewer.Viewer()
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viewer.data.set_mesh(V, F)
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viewer.core.show_lines = False
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viewer.data.set_colors(C)
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viewer.launch()
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