Example: Function call: ro_err(matrix_1, matrix_coeff).
matrix_1:
x1 |
x2 |
x3 |
x4 |
scenario_benchmark |
scenario_probability |
1 7 -2 0 |
4 -5 8 -3 |
8 4 -1 -4 |
3 -6 0 9 |
-2 11 6 10 |
0.2 0.2 0.3 0.3 |
matrix_coeff:
c1 |
c2 |
c3 |
c4 |
0.25 0.92 |
0.25 0.94 |
0.25 0.96 |
0.25 0.98 |
MATLAB code (./PSG/Example/Func_value_ro_err.m) for function minimization:
%Define data:
H1 = [1 4 8 3;7 -5 4 -6;-2 8 -1 0;0 -3 -4 9];
header_1 = {'x1', 'x2', 'x3', 'x4'};
c1 = [-2;11;6;10];
p1 = [0.2;0.2;0.3;0.3];
H2 = [0.25 0.25 0.25 0.25;0.92 0.94 0.96 0.98];
header_2 = {'c1', 'c2', 'c3', 'c4'};
%Create the PSG matrix 'matrix_1'(structure containing header and matrix body) and pack it to structure 'iargstruc_arr':
iargstruc_arr(1) = tbpsg_matrix_pack('matrix_1', H1, header_1, c1, p1);
%Create the PSG matrix 'matrix_2'(structure containing header and matrix body) and pack it to structure 'iargstruc_arr':
iargstruc_arr(2) = tbpsg_matrix_pack('matrix_coef', H2, header_2);
%Create problem statement:
problem_statement = sprintf('%s\n',...
'minimize',...
' ro_err(matrix_1,matrix_coef)',...
'');
%Minimize ro_err function with parameter 0.65 :
[solution_str, outargstruc_arr] = tbpsg_run(problem_statement, iargstruc_arr);
%Extract value of function from solution report:
val = tbpsg_function_data(solution_str, outargstruc_arr);
%Extract values of output points:
output = tbpsg_point_data(solution_str, outargstruc_arr);
%Display function value:
disp(' ')
disp(sprintf('ro_err function value = %g', val(1)));
disp(' ')
disp(sprintf('Pseudo R2 = %g', val(2)));
disp(' ')
disp('Contributions (normed increments) = ');
disp(output{2})
Program output:
ro_err function value = 1.36502e-013
Pseudo R2 = 1
Contributions (normed increments) =
0.4576 0.2558 0.1430 0.1436