examples/getting_started/plotting.cpp

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/*
 *    This file is part of ACADO Toolkit.
 *
 *    ACADO Toolkit -- A Toolkit for Automatic Control and Dynamic Optimization.
 *    Copyright (C) 2008-2014 by Boris Houska, Hans Joachim Ferreau,
 *    Milan Vukov, Rien Quirynen, KU Leuven.
 *    Developed within the Optimization in Engineering Center (OPTEC)
 *    under supervision of Moritz Diehl. All rights reserved.
 *
 *    ACADO Toolkit is free software; you can redistribute it and/or
 *    modify it under the terms of the GNU Lesser General Public
 *    License as published by the Free Software Foundation; either
 *    version 3 of the License, or (at your option) any later version.
 *
 *    ACADO Toolkit is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 *    Lesser General Public License for more details.
 *
 *    You should have received a copy of the GNU Lesser General Public
 *    License along with ACADO Toolkit; if not, write to the Free Software
 *    Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
 *
 */



#include <acado_toolkit.hpp>
#include <acado_gnuplot.hpp>


int main( ){

    USING_NAMESPACE_ACADO


        // DEFINE SAMPLE OCP
        // -----------------
        DifferentialState x, y;
        Control           u;

        DifferentialEquation f;
        
        f << dot(x) == y;
    f << dot(y) == u;

    OCP ocp( 0.0, 5.0 );
    ocp.minimizeLagrangeTerm( x*x + 0.01*u*u );

    ocp.subjectTo( f );
    ocp.subjectTo( AT_START, x ==  1.0 );
    ocp.subjectTo( AT_START, y ==  0.0 );

        ocp.subjectTo( -1.0 <= u <=  1.0 );


        // SETUP OPTIMIZATION ALGORITHM AND DEFINE VARIOUS PLOT WINDOWS
        // ------------------------------------------------------------
        OptimizationAlgorithm algorithm( ocp );

        GnuplotWindow window1;
        window1.addSubplot( x, "1st state" );
        window1.addSubplot( y, "2nd state","x label","y label",PM_POINTS );
        window1.addSubplot( u, "control input","x label","y label",PM_LINES,0,5,-2,2 );
        window1.addSubplot( 2.0*sin(x)+y*u, "Why not plotting fancy stuff!?" );
//      window1.addSubplot( PLOT_KKT_TOLERANCE, "","iteration","KKT tolerance" );
        
        GnuplotWindow window2( PLOT_AT_EACH_ITERATION );
        window2.addSubplot( x, "1st state evolving..." );
        
        algorithm << window1;
        algorithm << window2;
        
        algorithm.solve( );


        // For illustration, an alternative way to plot differential states
        // in form of a VariablesGrid
        VariablesGrid states;
        algorithm.getDifferentialStates( states );
        
        GnuplotWindow window3;
        window3.addSubplot( states(0), "1st state obtained as VariablesGrid" );
        window3.addSubplot( states(1), "2nd state obtained as VariablesGrid" );
        window3.plot();

        VariablesGrid data( 1, 0.0,10.0,11 );
        data.setZero();
        data( 2,0 ) = 1.0;
        data( 5,0 ) = -1.0;
        data( 8,0 ) = 2.0;
        data( 9,0 ) = 2.0;
        
//      data.setType( VT_CONTROL );
        
        GnuplotWindow window4;
        window4.addSubplot( data, "Any data can be plotted" );
        window4.plot();


    return 0;
}