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 2025.0.0. This page might be outdated.
However, this page did not exist in the previous stable version.
Optimization and Simulation
- Nonlinear Least Squares
- Semidefinite Programming
- aplat — Flattens a list.
- list2vec — リストのエントリを行列に連結する.
- lmisolver — LMIソルバー
- lmitool — LMIを解くためのツール
- pack — Compress a list of block-diagonal symmetric matrices.
- recons — Inverse function for aplat.
- semidef — Solve semidefinite problems.
- unpack — Uncompress a list of block-diagonal symmetric matrices.
- vec2list — Inverse function of list2vec.
- Neldermead
- fminsearch — Computes the unconstrained minimum of given function with the Nelder-Mead algorithm.
- neldermead — Provides direct search optimization algorithms.
- overview — An overview of the Nelder-Mead toolbox.
- nmplot — Provides direct search optimization algorithms.
- optimget — Queries an optimization data structure.
- optimplotfunccount — Plot the number of function evaluations of an optimization algorithm
- optimplotfval — Plot the function value of an optimization algorithm
- optimplotx — Plot the value of the parameters of an optimization algorithm
- optimset — Configures and returns an optimization data structure.
- Optimization base
- optimbase_cget — Returns the value for the given key.
- optimbase_checkbounds — Checks the bounds.
- optimbase_checkcostfun — Checks the cost function.
- optimbase_checkx0 — Checks initial guess.
- optimbase_configure — Configures the current object.
- optimbase_destroy — Resets the historyfopt and historyxopt fields of an object.
- optimbase_function — Calls cost function.
- optimbase_get — Returns the value for the given key.
- optimbase_hasbounds — Checks if the bounds are specified.
- optimbase_hasconstraints — Checks if the constraints are specified.
- optimbase_hasnlcons — Checks if the non linear constraints are specified.
- optimbase_histget — Returns the history value.
- optimbase_histset — Set the history value at given iteration for the given key.
- optimbase_incriter — Increments the number of iterations.
- optimbase_isfeasible — Checks if the point satisfies constraints.
- optimbase_isinbounds — Checks if the given point satisfies bounds constraints.
- optimbase_isinnonlincons — Checks if the given point satisfies the non-linear constraints.
- optimbase_log — Prints the given message.
- optimbase_new — Creates a new optimization object.
- optimbase_outputcmd — Calls back user's output command.
- optimbase_outstruct — Returns a data structure with type T_OPTDATA.
- overview — An overview of the Optimbase toolbox.
- optimbase_proj2bnds — Returns a projection point.
- optimbase_set — Set the value for the given key.
- optimbase_stoplog — Prints the given stopping message.
- optimbase_terminate — Checks if the algorithm is terminated.
- Simplex
- optimsimplex_center — Computes the center.
- optimsimplex_check — Checks the consistency of internal data
- optimsimplex_compsomefv — Computes the values of the function at vertices points.
- optimsimplex_computefv — Computes the values of the function at vertices points.
- optimsimplex_deltafv — Computes the difference of function values.
- optimsimplex_deltafvmax — Computes the difference of function value between the highest and the lowest vertices.
- optimsimplex_destroy — Destroys the simplex object.
- optimsimplex_dirmat — Computes the directions.
- optimsimplex_fvmean — Computes the mean.
- optimsimplex_fvstdev — Computes the standard deviation.
- optimsimplex_fvvariance — Computes the variance.
- optimsimplex_getall — Returns all the data contained in the simplex object.
- optimsimplex_getallfv — Returns all the function values contained in the simplex object.
- optimsimplex_getallx — Returns all the coordinates.
- optimsimplex_getfv — Returns the function value at given index.
- optimsimplex_getn — Returns the dimension of the space.
- optimsimplex_getnbve — Gets the number of vertices of the simplex.
- optimsimplex_getve — Gets the vertex at the given index.
- optimsimplex_getx — Gets the coordinates of the vertex at given index.
- optimsimplex_gradientfv — Returns the simplex gradient of the function.
- optimsimplex_new — Creates a new simplex object.
- overview — An overview of the Optimsimplex toolbox.
- optimsimplex_reflect — Returns the reflected simplex object.
- optimsimplex_setall — Sets all in the simplex object.
- optimsimplex_setallfv — Sets all the function values.
- optimsimplex_setallx — Sets all the coordinates.
- optimsimplex_setfv — Sets the function value at given index.
- optimsimplex_setn — Sets the dimension of the space.
- optimsimplex_setnbve — Sets the number of vertices of the simplex.
- optimsimplex_setve — Sets the data at given index in the current simplex.
- optimsimplex_setx — Sets the coordinates at given index into the current simplex.
- optimsimplex_shrink — Shrinks the simplex.
- optimsimplex_size — Computes the size.
- optimsimplex_sort — Sorts the simplex.
- optimsimplex_xbar — Returns the center of n vertices.
- fsolve — n個の非線形関数システムのゼロを見つける
- karmarkar — Solves a linear optimization problem.
- NDcost — generic external for optim computing gradient using finite differences
- optim — non-linear optimization routine
- qld — linear quadratic programming solver
- qp_solve — 組み込みの線形二次計画ソルバー
- qpsolve — 線形二次計画ソルバー
- readmps — Reads a Linear Program from a MPS file.
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