Scilab 5.5.0
- 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
- 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
- Intersci
- Preferences
- Windows tools
Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.
See the recommended documentation of this function
Optimization and Simulation
- Semidefinite Programming
- 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
- aplat — Flattens a list.
- 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 minimimum 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.
- Nonlinear Least Squares
- 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.
- Optimization 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 dimenson 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
- 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
- NDcost — generic external for optim computing gradient using finite differences
- derivative — approximate derivatives of a function. This function is obsolete. Please use the numderivative function instead.
- karmarkar — Solves a linear optimization problem.
- numderivative — approximate derivatives of a function (Jacobian or Hessian)
- optim — non-linear optimization routine
- qld — linear quadratic programming solver
- readmps — Reads a Linear Program from a MPS file.
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