Scilab 6.0.1
- Scilabヘルプ
- Scilab
- Differential Equations, Integration
- Elementary Functions
- Linear Algebra
- Interpolation
- CACSD
- Polynomials
- Signal Processing
- FFTW
- Special Functions
- Randlib
- 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
- Graphics : exporting and printing
- GUI
- Data Structures
- Parameters
- Boolean
- Integers
- Strings
- Sound file handling
- Time and Date
- Output functions
- Xcos
- Spreadsheet
- Console
- History manager
- Matlab binary files I/O
- Matlab to Scilab Conversion Tips
- Compatibility Functions
- Functions
- Development tools
- Demo Tools
- Dynamic/incremental Link
- Windows tools
- Atoms
- Tcl/Tk Interface
- scilab editor
- UI Data
- Online help management
- Parallel
- Modules manager
- Localization
- API Scilab
- call_scilab API
- JVM
- Java from Scilab
- Java Interface
- Preferences
- Lint tool (SLint)
Please note that the recommended version of Scilab is 2024.1.0. This page might be outdated.
However, this page did not exist in the previous stable version.
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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