| /petsc/src/vec/is/sf/tests/ |
| H A D | ex5.c | 87 PetscBool inverse = PETSC_FALSE, test_vector = PETSC_TRUE; in main() local 92 PetscCall(PetscOptionsGetBool(NULL, NULL, "-explicit_inverse", &inverse, NULL)); in main() 199 if (!inverse) { in main() 216 if (!inverse) { in main()
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| /petsc/src/ksp/ksp/utils/lmvm/tests/ |
| H A D | ex1.c | 23 static PetscErrorCode HermitianTransposeTest(Mat B, PetscRandom rand, PetscBool inverse) in HermitianTransposeTest() argument 36 PetscCall((inverse ? MatSolve : MatMult)(B, x, Bx)); in HermitianTransposeTest() 37 PetscCall((inverse ? MatSolveHermitianTranspose : MatMultHermitianTranspose)(B, f, Bhf)); in HermitianTransposeTest() 80 static PetscErrorCode IsHermitianTest(Mat B, PetscRandom rand, PetscBool inverse) in IsHermitianTest() argument 94 PetscCall((inverse ? MatSolve : MatMult)(B, x, Bx)); in IsHermitianTest() 95 PetscCall((inverse ? MatSolve : MatMult)(B, y, By)); in IsHermitianTest()
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| /petsc/doc/manual/ |
| H A D | dt.md | 17 …domain for $x$. This requires that the PDF must have units which are the inverse of the volume for…
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| H A D | tao.md | 489 are the constraint Jacobian and its pseudo-inverse (optional), respectively. The 703 and for applying the inverse of the state Jacobian, respectively. This 704 inverse matrix may be `PETSC_NULL`, in which case TAO will use a PETSc 721 for the inverse of the state Jacobian. One can use `PETSC_NULL` for 722 this inverse argument and let PETSc apply the inverse using a KSP 724 of the Jacobian and providing an inverse. The fifth argument is the 727 no need to provide preconditioner or inverse matrices. 1121 of the inverse Hessian. See the PETSc manual for further information on 1539 BFGS update formula. The inverse of $H_k$ can readily be applied 1740 diagonal matrix $D_k$ is an approximation of the Hessian inverse [all …]
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| H A D | mat.md | 532 explicit Jacobian, and instead compute forward products and inverse 594 forward/inverse applications. The `X` vector defines the solution 611 `MatMult()` or `MatMultAdd()`, and in inverse mode via
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| H A D | ksp.md | 1434 …attern, or try to determine adaptively, as is done in sparse approximate inverse preconditioning. … 2212 Schur complements. The inverse of the Schur complement factorization is 2358 By default $\text{inv}(A_{00})$ is the inverse of the diagonal of 2363 inverse of the block diagonal of $A_{00}$. Option
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| H A D | ts.md | 1101 While the true mass matrix generally has a dense inverse and thus must be solved iteratively, the l…
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| /petsc/src/dm/impls/plex/ |
| H A D | plexpreallocate.c | 23 PetscInt p, q, a, aSize, *offsets, aStart, aEnd, *inverse, iSize, *adj, adjSize; in DMPlexComputeAnchorAdjacencies() local 40 PetscCall(PetscMalloc1(iSize, &inverse)); in DMPlexComputeAnchorAdjacencies() 54 inverse[iOff + offsets[a - pStart]++] = p; in DMPlexComputeAnchorAdjacencies() 87 q = inverse[iOff + i]; in DMPlexComputeAnchorAdjacencies() 121 q = inverse[iOff + i]; in DMPlexComputeAnchorAdjacencies() 143 PetscCall(PetscFree(inverse)); in DMPlexComputeAnchorAdjacencies()
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| /petsc/src/binding/petsc4py/docs/source/ |
| H A D | petsc_python_types.rst | 46 pointwise multiplication of the inverse diagonal with the input vector.
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| /petsc/doc/install/ |
| H A D | external_software.md | 31 …enceworkentry/10.1007%2F978-0-387-09766-4_144) Parallel sparse approximate inverse preconditioning.
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| /petsc/doc/miscellaneous/ |
| H A D | acknowledgements.md | 86 - SPAI - for parallel sparse approximate inverse preconditioning;
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| /petsc/src/binding/petsc4py/src/petsc4py/PETSc/ |
| H A D | SF.pyx | 263 """Create the inverse map. 267 Create the inverse map given a PetscSF in which all vertices have
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| H A D | DMLabel.pyx | 591 This is the inverse operation to `distribute`.
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| H A D | TAO.pyx | 1527 """Return the `KSP` for the inverse of the initial Hessian approximation.
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| H A D | Mat.pyx | 3732 """Return the inverse of the block-diagonal entries.
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| /petsc/doc/ |
| H A D | index.md | 88 for solving deterministic and Bayesian inverse
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| H A D | petsc.bib | 1956 note = {Winner of SC2002 Best Paper. A parallel algorithm for inverse problems governed 1957 by time-dependent PDEs, and scalability results for an inverse wave propagation 1959 algorithm, they solved a synthetic inverse wave propagation problem though a 2875 title = {Hierarchical matrix approximations of {Hessians} arising in inverse problems 3321 title = {Application of hierarchical matrices to linear inverse problems in 3543 keywords = {geophysical image processing; inverse problems; seismology}, 4597 preconditioner, the ability to solve inverse problems with up to 17 million 4740 url = {http://www.cs.cmu.edu/\~{ }oghattas/papers/sc05-inverse.pdf}, 7183 title = {A numerical method for inverse design based on the inverse Euler equations}, 9976 inverse problems based on low-rank partial {H}essian approximations}, [all …]
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| /petsc/doc/changes/ |
| H A D | 312.md | 109 inverse of an SF under the another SF.
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| /petsc/doc/faq/ |
| H A D | index.md | 971 ### How can I compute the inverse of a matrix in PETSc? 976 It is very expensive to compute the inverse of a matrix and very rarely needed in 980 The inverse of a matrix (dense or sparse) is essentially always dense, so begin by 984 result A. Then call `MatMatSolve(A,B,X)` to compute the inverse into X. See also section 1021 Like the inverse, the Schur complement of a matrix (dense or sparse) is essentially always
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| /petsc/share/petsc/datafiles/meshes/ |
| H A D | testcase3D.cas | 8511 (clipped-node/inverse-dist? #f)
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