-c = [350*5,330*3,310*4,280*6,500,450,400,100]
+c = [350*5,330*3,310*4,280*6,500,450,400,100]';
lb = repmat(0,1,8);
@@ -109,7 +111,7 @@ find the minimum or maximum of f(x) such that
957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 ..
959 668 507 855 986 831 821 825 868 852 832 828 799 686 ..
510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 ..
-1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]
+1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]';
conMatrix = [
42 41 523 215 819 551 69 193 582 375 367 478 162 898 ..
diff --git a/help/en_US/symphony.xml b/help/en_US/symphony.xml
index 972bfc1..a80f022 100644
--- a/help/en_US/symphony.xml
+++ b/help/en_US/symphony.xml
@@ -40,7 +40,7 @@
nbCon :
a double, number of constraints.
objCoeff :
- a 1 x n matrix of doubles, where n is number of variables, represents coefficients of the variables in the objective.
+ a vector of doubles, represents coefficients of the variables in the objective.
isInt :
a vector of boolean, represents wether a variable is constrained to be an integer.
LB :
diff --git a/help/en_US/symphonymat.xml b/help/en_US/symphonymat.xml
index 1328167..881092b 100644
--- a/help/en_US/symphonymat.xml
+++ b/help/en_US/symphonymat.xml
@@ -37,7 +37,7 @@
Parameters
f :
- a vector of doubles, where n is number of variables, contains coefficients of the variables in the objective
+ a vector of doubles, contains coefficients of the variables in the objective
intcon :
Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable.
A :
@@ -55,9 +55,11 @@
options :
a list containing the the parameters to be set.
xopt :
- a 1xn matrix of doubles, the computed solution of the optimization problem
+ a vector of double, the computed solution of the optimization problem
fopt :
- a 1x1 matrix of doubles, the function value at x
+ a doubles, the function value at x
+ status :
+ status flag from symphony.
output :
The output data structure contains detailed informations about the optimization process.
@@ -91,7 +93,7 @@ We are calling SYMPHONY written in C by gateway files for the actual computation
Examples
// \begin{eqnarray}
@@ -212,7 +212,7 @@ function [xopt,resnorm,residual,exitflag,output,lambda] = lsqlin (varargin)
x0=x0';
end
- //Check the size of f which should equal to the number of variable
+ //Check the size of d which should equal to the number of variable
if ( size(d,1) ~= size(C,1)) then
errmsg = msprintf(gettext("%s: The number of rows in C must be equal the number of elements of d"), "lsqlin");
error(errmsg);
diff --git a/macros/lsqnonneg.bin b/macros/lsqnonneg.bin
new file mode 100644
index 0000000..e9e1295
Binary files /dev/null and b/macros/lsqnonneg.bin differ
diff --git a/macros/lsqnonneg.sci b/macros/lsqnonneg.sci
new file mode 100644
index 0000000..c65b1ba
--- /dev/null
+++ b/macros/lsqnonneg.sci
@@ -0,0 +1,186 @@
+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// Author: Harpreet Singh
+// Organization: FOSSEE, IIT Bombay
+// Email: harpreet.mertia@gmail.com
+// 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
+
+
+function [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg (varargin)
+ // Solves nonnegative least-squares curve fitting problems.
+ //
+ // Calling Sequence
+ // x = lsqnonneg(C,d)
+ // x = lsqnonneg(C,d,param)
+ // [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg( ... )
+ //
+ // Parameters
+ // C : a matrix of doubles, represents the multiplier of the solution x in the expression C*x - d. C is M-by-N, where M is the number of equations, and N is the number of elements of x.
+ // d : a vector of doubles, represents the additive constant term in the expression C*x - d. d is M-by-1, where M is the number of equations.
+ // xopt : a vector of doubles, the computed solution of the optimization problem.
+ // resnorm : a double, objective value returned as the scalar value norm(C*x-d)^2.
+ // residual : a vector of doubles, solution residuals returned as the vector C*x-d.
+ // exitflag : Integer identifying the reason the algorithm terminated.
+ // output : Structure containing information about the optimization.
+ // lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).
+ //
+ // Description
+ // Solves nonnegative least-squares curve fitting problems specified by :
+ //
+ //
+ // \begin{eqnarray}
+ // &\mbox{min}_{x}
+ // & 1/2||C*x - d||_2^2 \\
+ // & & x \geq 0 \\
+ // \end{eqnarray}
+ //
+ //
+ // We are calling IPOpt for solving the nonnegative least-squares curve fitting problems, IPOpt is a library written in C++. The code has been written by Andreas Wächter and Carl Laird.
+ //
+ // Examples
+ // A basic lsqnonneg problem
+ // C = [
+ // 0.0372 0.2869
+ // 0.6861 0.7071
+ // 0.6233 0.6245
+ // 0.6344 0.6170];
+ // d = [
+ // 0.8587
+ // 0.1781
+ // 0.0747
+ // 0.8405];
+ // [xopt,resnorm,residual,exitflag,output,lambda] = lsqnonneg(C,d)
+ //
+ // Authors
+ // Harpreet Singh
+
+
+ //To check the number of input and output argument
+ [lhs , rhs] = argn();
+
+ //To check the number of argument given by user
+ if ( rhs < 2 | rhs > 3 ) then
+ errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 3]"), "lsqlin", rhs);
+ error(errmsg)
+ end
+
+ C = varargin(1);
+ d = varargin(2);
+ nbVar = size(C,2);
+ if ( rhs<3 | size(varargin(3)) ==0 ) then
+ param = list();
+ else
+ param =varargin(10);
+ end
+
+ if (type(param) ~= 15) then
+ errmsg = msprintf(gettext("%s: param should be a list "), "lsqlin");
+ error(errmsg);
+ end
+
+
+ if (modulo(size(param),2)) then
+ errmsg = msprintf(gettext("%s: Size of parameters should be even"), "lsqlin");
+ error(errmsg);
+ end
+
+ options = list( "MaxIter" , [3000], ...
+ "CpuTime" , [600] ...
+ );
+
+ for i = 1:(size(param))/2
+
+ select param(2*i-1)
+ case "MaxIter" then
+ options(2*i) = param(2*i);
+ case "CpuTime" then
+ options(2*i) = param(2*i);
+ else
+ errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "lsqlin", param(2*i-1));
+ error(errmsg)
+ end
+ end
+
+ // Check if the user gives row vector
+ // and Changing it to a column matrix
+
+
+ if (size(d,2)== [nbVar]) then
+ d=d';
+ end
+
+ //Check the size of f which should equal to the number of variable
+ if ( size(d,1) ~= size(C,1)) then
+ errmsg = msprintf(gettext("%s: The number of rows in C must be equal the number of elements of d"), "lsqlin");
+ error(errmsg);
+ end
+
+ //Converting it into Quadratic Programming Problem
+
+ Q = C'*C;
+ p = [-C'*d]';
+ op_add = d'*d;
+ LB = repmat(0,1,nbVar);
+ UB = repmat(%inf,1,nbVar);
+ x0 = repmat(0,1,nbVar);;
+ conMatrix = [];
+ nbCon = size(conMatrix,1);
+ conLB = [];
+ conUB = [] ;
+ [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options);
+
+ xopt = xopt';
+ residual = C*xopt-d;
+ resnorm = residual'*residual;
+ exitflag = status;
+ output = struct("Iterations" , []);
+ output.Iterations = iter;
+ lambda = struct("lower" , [], ..
+ "upper" , [], ..
+ "constraint" , []);
+
+ lambda.lower = Zl;
+ lambda.upper = Zu;
+ lambda.constraint = lmbda;
+
+ select status
+ case 0 then
+ printf("\nOptimal Solution Found.\n");
+ case 1 then
+ printf("\nMaximum Number of Iterations Exceeded. Output may not be optimal.\n");
+ case 2 then
+ printf("\nMaximum CPU Time exceeded. Output may not be optimal.\n");
+ case 3 then
+ printf("\nStop at Tiny Step\n");
+ case 4 then
+ printf("\nSolved To Acceptable Level\n");
+ case 5 then
+ printf("\nConverged to a point of local infeasibility.\n");
+ case 6 then
+ printf("\nStopping optimization at current point as requested by user.\n");
+ case 7 then
+ printf("\nFeasible point for square problem found.\n");
+ case 8 then
+ printf("\nIterates diverging; problem might be unbounded.\n");
+ case 9 then
+ printf("\nRestoration Failed!\n");
+ case 10 then
+ printf("\nError in step computation (regularization becomes too large?)!\n");
+ case 12 then
+ printf("\nProblem has too few degrees of freedom.\n");
+ case 13 then
+ printf("\nInvalid option thrown back by IPOpt\n");
+ case 14 then
+ printf("\nNot enough memory.\n");
+ case 15 then
+ printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify IPOPT Authors.\n");
+ else
+ printf("\nInvalid status returned. Notify the Toolbox authors\n");
+ break;
+ end
+
+endfunction
diff --git a/macros/names b/macros/names
index 18923c4..e04f783 100644
--- a/macros/names
+++ b/macros/names
@@ -1,8 +1,8 @@
lsqlin
+lsqnonneg
qpipopt
qpipoptmat
setOptions
symphony
symphony_call
-symphony_mat
symphonymat
diff --git a/macros/qpipopt.bin b/macros/qpipopt.bin
index e13d5a9..2fd432e 100644
Binary files a/macros/qpipopt.bin and b/macros/qpipopt.bin differ
diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci
index ccf10e4..8b7cecd 100644
--- a/macros/qpipopt.sci
+++ b/macros/qpipopt.sci
@@ -25,7 +25,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
// Q : a symmetric matrix of doubles, represents coefficients of quadratic in the quadratic problem.
// p : a vector of doubles, represents coefficients of linear in the quadratic problem
// LB : a vector of doubles, contains lower bounds of the variables.
- // UB : a vector of doubles, where n is number of variables, contains upper bounds of the variables.
+ // UB : a vector of doubles, contains upper bounds of the variables.
// conMatrix : a matrix of doubles, contains matrix representing the constraint matrix
// conLB : a vector of doubles, contains lower bounds of the constraints.
// conUB : a vector of doubles, contains upper bounds of the constraints.
diff --git a/macros/qpipoptmat.bin b/macros/qpipoptmat.bin
index 07c9386..98ec979 100644
Binary files a/macros/qpipoptmat.bin and b/macros/qpipoptmat.bin differ
diff --git a/macros/qpipoptmat.sci b/macros/qpipoptmat.sci
index 9f20870..4b8e427 100644
--- a/macros/qpipoptmat.sci
+++ b/macros/qpipoptmat.sci
@@ -29,8 +29,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin)
// b : a vector of doubles, represents the linear coefficients in the inequality constraints
// Aeq : a matrix of doubles, represents the linear coefficients in the equality constraints
// beq : a vector of doubles, represents the linear coefficients in the equality constraints
- // LB : a vector of doubles, where n is number of variables, contains lower bounds of the variables.
- // UB : a vector of doubles, where n is number of variables, contains upper bounds of the variables.
+ // LB : a vector of doubles, contains lower bounds of the variables.
+ // UB : a vector of doubles, contains upper bounds of the variables.
// x0 : a vector of doubles, contains initial guess of variables.
// param : a list containing the the parameters to be set.
// xopt : a vector of doubles, the computed solution of the optimization problem.
diff --git a/macros/symphony.bin b/macros/symphony.bin
index d126d9f..3dab926 100644
Binary files a/macros/symphony.bin and b/macros/symphony.bin differ
diff --git a/macros/symphony.sci b/macros/symphony.sci
index c5b1cdf..eba9e64 100644
--- a/macros/symphony.sci
+++ b/macros/symphony.sci
@@ -21,7 +21,7 @@ function [xopt,fopt,status,output] = symphony (varargin)
// Parameters
// nbVar : a double, number of variables.
// nbCon : a double, number of constraints.
- // objCoeff : a 1 x n matrix of doubles, where n is number of variables, represents coefficients of the variables in the objective.
+ // objCoeff : a vector of doubles, represents coefficients of the variables in the objective.
// isInt : a vector of boolean, represents wether a variable is constrained to be an integer.
// LB : a vector of doubles, represents lower bounds of the variables.
// UB : a vector of doubles, represents upper bounds of the variables.
diff --git a/macros/symphonymat.bin b/macros/symphonymat.bin
index 95bba1a..8d42926 100644
Binary files a/macros/symphonymat.bin and b/macros/symphonymat.bin differ
diff --git a/macros/symphonymat.sci b/macros/symphonymat.sci
index 9e1ffaf..33a1163 100644
--- a/macros/symphonymat.sci
+++ b/macros/symphonymat.sci
@@ -20,7 +20,7 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
// [xopt,fopt,status,output] = symphonymat( ... )
//
// Parameters
- // f : a vector of doubles, where n is number of variables, contains coefficients of the variables in the objective
+ // f : a vector of doubles, contains coefficients of the variables in the objective
// intcon : Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable.
// A : Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables
// b : Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N
@@ -29,8 +29,9 @@ function [xopt,fopt,status,iter] = symphonymat (varargin)
// lb : Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub.
// ub : Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub.
// options : a list containing the the parameters to be set.
- // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem
- // fopt : a 1x1 matrix of doubles, the function value at x
+ // xopt : a vector of double, the computed solution of the optimization problem
+ // fopt : a doubles, the function value at x
+ // status : status flag from symphony.
// output : The output data structure contains detailed informations about the optimization process.
//
// Description
--
cgit
|
