## Group Hardesty

Group Description |
Surface fitting problem for visualization, Sean Hardesty Visualization of 3D structures in the earth The Hardesty3 matrix is an interpolation matrix stacked above a weighted Laplacian, to to fit a surface z(x,y) to a set of points in R^3 subject to a smoothness constraint enforced via regularization. Hardesty2 is a smaller version of this problem. For the big matrix (Hardesty/Hardesty3), sparse QR (via SuiteSparseQR, or SPQR) finds an R factor and a set of Householder vectors (Q.H) with about 150 million nonzeros. Sparse LU factorization (with UMFPACK v5.7.1) sees very high fillin (about 2.5 billion nonzeros in L+U). The Hardesty1 matrix is a simple discretization of a 2D biharmonic operator with some Lagrange multiplier constraints used for smoothing. |
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Displaying

**all 3**collection matricesId | Name | Group | Rows | Cols | Nonzeros | Kind | Date | Download File |
---|---|---|---|---|---|---|---|---|

2832 | Hardesty2 | Hardesty | 929,901 | 303,645 | 4,020,731 | Computer Graphics/Vision Problem | 2015 | MATLAB Rutherford Boeing Matrix Market |

2831 | Hardesty1 | Hardesty | 938,905 | 938,905 | 12,143,314 | Computer Graphics/Vision Problem | 2013 | MATLAB Rutherford Boeing Matrix Market |

2833 | Hardesty3 | Hardesty | 8,217,820 | 7,591,564 | 40,451,632 | Computer Graphics/Vision Problem | 2015 | MATLAB Rutherford Boeing Matrix Market |