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diff --git a/macros/fseminf.sci b/macros/fseminf.sci deleted file mode 100644 index 2ffcab5..0000000 --- a/macros/fseminf.sci +++ /dev/null @@ -1,322 +0,0 @@ -// Copyright (C) 2015 - IIT Bombay - FOSSEE -// -// This file must be used under the terms of the CeCILL. -// This source file is licensed as described in the file COPYING, which -// you should have received as part of this distribution. The terms -// are also available at -// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt -// Author: Salman Anis, Harpreet Singh -// Organization: FOSSEE, IIT Bombay -// Email: toolbox@scilab.in - -function [xopt,fopt,exitflag,output,lambda,gradient,hessian] = fseminf (varargin) - // Solves a multi-variable constrainted optimization problem - // - // Calling Sequence - // xopt = fseminf(fun,x0,ntheta,seminfcon) - // xopt = fseminf(fun,x0,ntheta,seminfcon,A,b) - // xopt = fseminf(fun,x0,ntheta,seminfcon,A,b,Aeq,beq) - // xopt = fseminf(fun,x0,ntheta,seminfcon,A,b,Aeq,beq,lb,ub) - // xopt = fseminf(fun,x0,ntheta,seminfcon,A,b,Aeq,beq,lb,ub,options) - // [xopt,fopt] = fseminf(.....) - // [xopt,fopt,exitflag]= fseminf(.....) - // [xopt,fopt,exitflag,output]= fseminf(.....) - // [xopt,fopt,exitflag,output,lambda]=fseminf(.....) - // [xopt,fopt,exitflag,output,lambda]=fseminf(.....) - // [xopt,fopt,exitflag,output,lambda]=fseminf(.....) - // - // Parameters - // fun : a function, representing the objective function of the problem - // x0 : a vector of doubles, containing the starting values of variables of size (1 X n) or (n X 1) where 'n' is the number of Variables - // ntheta : The number of semi-infinite constraints. - // seminfcon : a function that calculates the vector of nonlinear inequality constraints c, a vector of nonlinear equality constraints ceq, and ntheta semi-infinite constraints. See below for details. - // A : a matrix of double, represents the linear coefficients in the inequality constraints A⋅x ≤ b. - // b : a vector of double, represents the linear coefficients in the inequality constraints A⋅x ≤ b. - // Aeq : a matrix of double, represents the linear coefficients in the equality constraints Aeq⋅x = beq. - // beq : a vector of double, represents the linear coefficients in the equality constraints Aeq⋅x = beq. - // lb : a vector of double, contains lower bounds of the variables. - // ub : a vector of double, contains upper bounds of the variables. - // options : a list, containing the option for user to specify. See below for details. - - // xopt : a vector of double, the computed solution of the optimization problem. - // fopt : a double, the value of the function at x. - // exitflag : The exit status. See below for details. - // output : The structure consist of statistics about the optimization. See below for details. - // lambda : The structure consist of the Lagrange multipliers at the solution of problem. See below for details. - // - // Description - // Search the minimum of a constrained optimization problem specified by : - // Find the minimum of f(x) such that - // - // <latex> - // \begin{eqnarray} - // &\mbox{min}_{x} - // & f(x) \\ - // & \text{subject to} & A*x \leq b \\ - // & & Aeq*x \ = beq\\ - // & & lb \leq x \leq ub \\ - // & & c(x) \leq 0\\ - // & & ceq(x) \ = 0\\ - // & & K_i(x,w_i) \leq 0, 1 \leq i \leq n. - // \end{eqnarray} - // </latex> - // - // The routine calls Ipopt for solving the Constrained Optimization problem, Ipopt is a library written in C++. - // - // The options allows the user to set various parameters of the Optimization problem. - // It should be defined as type "list" and contains the following fields. - // <itemizedlist> - // <listitem>Syntax : options= list("MaxIter", [---], "CpuTime", [---], "GradObj", ---);</listitem> - // <listitem>MaxIter : a Scalar, containing the Maximum Number of Iteration that the solver should take.</listitem> - // <listitem>CpuTime : a Scalar, containing the Maximum amount of CPU Time that the solver should take.</listitem> - // <listitem>GradObj : a function, representing the gradient function of the Objective in Vector Form.</listitem> - // <listitem>Default Values : options = list("MaxIter", [3000], "CpuTime", [600]);</listitem> - // </itemizedlist> - // - // The exitflag allows to know the status of the optimization which is given back by Ipopt. - // <itemizedlist> - // <listitem>exitflag=0 : Optimal Solution Found </listitem> - // <listitem>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</listitem> - // <listitem>exitflag=2 : Maximum amount of CPU Time exceeded. Output may not be optimal.</listitem> - // <listitem>exitflag=3 : Stop at Tiny Step.</listitem> - // <listitem>exitflag=4 : Solved To Acceptable Level.</listitem> - // <listitem>exitflag=5 : Converged to a point of local infeasibility.</listitem> - // </itemizedlist> - // - // For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/ - // - // The output data structure contains detailed informations about the optimization process. - // It has type "struct" and contains the following fields. - // <itemizedlist> - // <listitem>output.Iterations: The number of iterations performed during the search</listitem> - // <listitem>output.Cpu_Time: The total cpu-time spend during the search</listitem> - // <listitem>output.Objective_Evaluation: The number of Objective Evaluations performed during the search</listitem> - // <listitem>output.Dual_Infeasibility: The Dual Infeasiblity of the final soution</listitem> - // </itemizedlist> - // - // The lambda data structure contains the Lagrange multipliers at the end - // of optimization. In the current version the values are returned only when the the solution is optimal. - // It has type "struct" and contains the following fields. - // <itemizedlist> - // <listitem>lambda.lower: The Lagrange multipliers for the lower bound constraints.</listitem> - // <listitem>lambda.upper: The Lagrange multipliers for the upper bound constraints.</listitem> - // <listitem>lambda.eqlin: The Lagrange multipliers for the linear equality constraints.</listitem> - // <listitem>lambda.ineqlin: The Lagrange multipliers for the linear inequality constraints.</listitem> - // <listitem>lambda.eqnonlin: The Lagrange multipliers for the non-linear equality constraints.</listitem> - // <listitem>lambda.ineqnonlin: The Lagrange multipliers for the non-linear inequality constraints.</listitem> - // </itemizedlist> - // - // Examples - // function [y] = obj(x) - // y = (x-1)^2; - // endfunction - // function [c, ceq, K1, s] = seminfcon(x,s) - // // No finite nonlinear inequality and equality constraints - // c = []; - // ceq = []; - // // Sample set - // if isnan(s) - // // Initial sampling interval - // s = [0.01 0]; - // end - // t = 0:s(1):1; - // // Evaluate the semi-infinite constraint - // K1 = (x - 0.5) - (t - 0.5).^2; - // endfunction - // x = fseminf(obj,0.2,1,seminfcon) - // - // Authors - // Salman Anis, Harpreet Singh - - - //To check the number of input and output arguments - [lhs , rhs] = argn(); - - //To check the number of arguments given by the user - if ( rhs<4 | rhs==5 | rhs==7 | rhs>13 ) then - errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while it should be 4,6,8,10,11"), "fseminf", rhs); - error(errmsg) - end - - //Storing the Input Parameters - _fun = varargin(1); - x0 = varargin(2); - ntheta = varargin(3); - seminfcon = varargin(4); - nbVar = size(x0,'*'); - - if(nbVar == 0) then - errmsg = msprintf(gettext("%s: Cannot determine the number of variables because input initial guess is empty"), "lsqcurvefit"); - error(errmsg); - end - - A = []; - b = []; - Aeq = []; - beq = []; - lb = []; - ub = []; - nlc = []; - param = list(); - - if (rhs>4) then - A = varargin(5); - b = varargin(6); - end - - if (rhs>6) then - Aeq = varargin(7); - beq = varargin(8); - end - - if (rhs>8) then - lb = varargin(9); - ub = varargin(10); - end - - if (rhs>10) then - param = varargin(10); - end - - if (size(lb,2)==0) then - lb = repmat(-%inf,nbVar,1); - end - - if (size(ub,2)==0) then - ub = repmat(%inf,nbVar,1); - end - - //Check type of variables - Checktype("fseminf", _fun, "fun", 1, "function") - Checktype("fseminf", x0, "x0", 2, "constant") - Checktype("fseminf", ntheta, "ntheta", 3, "constant") - Checktype("fseminf", seminfcon, "seminfcon", 4, ["function","constant"]) - Checktype("fseminf", A, "A", 5, "constant") - Checktype("fseminf", b, "b", 6, "constant") - Checktype("fseminf", Aeq, "Aeq", 7, "constant") - Checktype("fseminf", beq, "beq", 8, "constant") - Checktype("fseminf", lb, "lb", 9, "constant") - Checktype("fseminf", ub, "ub", 10, "constant") - Checktype("fseminf", param, "param", 10, "list") - - //To check the user entry for options and storing it - for i = 1:(size(param))/2 - select convstr(param(2*i-1),'l') - case "maxiter" then - Checktype("fseminf", param(2*i), "maxiter", 10, "constant") - options(2) = param(2*i); //Setting the maximum number of iterations as per user entry - case "cputime" then - Checktype("fseminf", param(2*i), "cputime", 10, "constant") - options(4) = param(2*i); //Setting the maximum CPU time as per user entry - case "gradobj" then - Checktype("fseminf", param(2*i), "gradobj", 10, "string") - if(convstr(param(2*i),'l') == "on") then - function dy = graObj(x) - - endfunction - end - else - errmsg = msprintf(gettext("%s: Unrecognized parameter name %s."), "fmincon", param(2*i-1)); - error(errmsg); - end - end - - //To check and convert the 2nd Input argument (x0) to a row vector - if((size(x0,1)~=1) & (size(x0,2)~=1)) then - errmsg = msprintf(gettext("%s: Expected Vector for initial guess"), "fseminf"); - error(errmsg); - end - - if(size(x0,2)==1) then - x0=x0(:); - end - - //To check the match between fun (1st Parameter) and x0 (2nd Parameter) - if(execstr('init=_fun(x0)','errcatch')==21) then - errmsg = msprintf(gettext("%s: Objective function and x0 did not match"), "fseminf"); - error(errmsg); - end - - //Check the size of inequality constraint which should be equal to the number of variables - if ( size(A,2) ~= nbVar & size(A,2) ~= 0) then - errmsg = msprintf(gettext("%s: The number of columns in A must be the same as the number of elements of x0"), "fseminf"); - error(errmsg); - end - - nbConInEq = size(A,"r"); - - //Check the size of equality constraint which should be equal to the number of variables - if ( size(Aeq,2) ~= nbVar & size(Aeq,2) ~= 0 ) then - errmsg = msprintf(gettext("%s: The number of columns in Aeq must be the same as the number of elements of f"), "fseminf"); - error(errmsg); - end - - b = b(:); - beq = beq(:); - lb = lb(:); - ub = ub(:); - - //To check the contents of lb & ub - for i = 1:nbVar - if(ub(i)<lb(i)) then - errmsg = msprintf(gettext("%s: Problem has inconsistent variable bounds"), "fseminf"); - error(errmsg); - end - end - - if(typeof(seminfcon) == "function") - sample_S = %nan - if(execstr('[sample_c,sample_ceq,sample_K,sample_S] = seminfcon(x0,sample_S)','errcatch')==21) - errmsg = msprintf(gettext("%s: Semi-Infinite Constraint function & x0 did not match"), "fseminf"); - error(errmsg); - end - [sample_c, sample_ceq, sample_K, sample_S] = seminfcon(x0,sample_S); - - if (size(sample_c,1)~=1 & size(sample_c,1)~=0) then - errmsg = msprintf(gettext("%s: c in seminfcon should be a row vector or empty matrix"), "fseminf"); - error(errmsg) - end - - if (size(sample_ceq,1)~=1 & size(sample_ceq,1)~=0) then - errmsg = msprintf(gettext("%s: ceq in seminfcon should be a row vector or empty matrix"), "fseminf"); - error(errmsg) - end - - if (size(sample_K,"r")~=ntheta) then - errmsg = msprintf(gettext("%s: Number of rows in K should be equal to ntheta"), "fseminf"); - error(errmsg) - end - - if (size(sample_S,"c")~=2) then - errmsg = msprintf(gettext("%s: Number of columns in sampling interval should be equal to 2"), "fseminf"); - error(errmsg) - end - end - - ierr = execstr('init=_fun(x0)', "errcatch") - if ierr <> 0 then - lamsg = lasterror(); - lclmsg = "%s: Error while evaluating the function: ""%s""\n"; - error(msprintf(gettext(lclmsg), "fseminf", lamsg)); - end - - S = %nan; - - ierr = execstr('init=seminfcon(x0,S)', "errcatch") - if ierr <> 0 then - lamsg = lasterror(); - lclmsg = "%s: Error while evaluating the function: ""%s""\n"; - error(msprintf(gettext(lclmsg), "fseminf", lamsg)); - end - - function [c, ceq] = _seminfcon(x) - [c, ceq, K, S] = seminfcon(x,S) - K_max = max(K,"c"); - c= [c;K_max]; - ceq = ceq; - endfunction - - //Calling the fmincon function for solving the above problem - [xopt,fopt,exitflag,output,lambda,gradient] = fmincon(_fun,x0,A,b,Aeq,beq,lb,ub,_seminfcon,param) - -endfunction |