Scilab 6.0.2
- Scilabヘルプ
- Scilab
- Differential Equations, Integration
- Elementary Functions
- Linear Algebra
- Interpolation
- CACSD
- Polynomials
- Signal Processing
- FFTW
- Special Functions
- ARnoldi PACKage
- Statistics
- Sparses Matrix
- UMFPACK Interface
- Optimization and Simulation
- Genetic Algorithms
- Simulated Annealing
- XML Management
- HDF5 Management
- Files : Input/Output functions
- Input/Output functions
- Graphics
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- Integers
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- Sound file handling
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- Xcos
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- Matlab binary files I/O
- Matlab to Scilab Conversion Tips
- Compatibility Functions
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- Dynamic/incremental Link
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- Localization
- API Scilab
- call_scilab API
- JVM
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- Preferences
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- Lint tool (SLint)
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Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.
See the recommended documentation of this function
UMFPACK Interface
- cond2sp — computes an approximation of the 2-norm condition number of a s.p.d. sparse matrix
- condestsp — estimate the condition number of a sparse matrix
- PlotSparse — plot the pattern of non nul elements of a sparse matrix
- ReadHBSparse — read a Harwell-Boeing sparse format file
- res_with_prec — computes the residual r = Ax-b with precision
- taucs_chdel — utility function used with taucs_chfact
- taucs_chfact — cholesky factorization of a sparse s.p.d. matrix
- taucs_chget — retrieve the Cholesky factorization at the scilab level
- taucs_chinfo — get information on Cholesky factors
- taucs_chsolve — solves a linear s.p.d. system A*X = B from Cholesky factors of the sparse A
- umf_ludel — utility function used with umf_lufact
- umf_lufact — lu factorization of a sparse matrix
- umf_luget — retrieve lu factors at the Scilab level
- umf_luinfo — get information on LU factors
- umf_lusolve — solve a linear sparse system given the LU factors
- umfpack — solve sparse linear system
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